# ”Can I Touch This?”: Survey of Virtual Reality Interactions via Haptic
Solutions

Revue de Littérature des Interactions en Réalité Virtuelle par le biais de
Solutions Haptiques

Elodie Bouzbib  ISIR. Sorbonne UniversitéISCD. Sorbonne UniversitéParisFrance
,  Gilles Bailly  ,  Sinan Haliyo  ISIR. Sorbonne UniversitéParisFrance and
Pascal Frey  ISCD. Sorbonne UniversitéParisFrance

(2021)

###### Abstract.

Haptic feedback has become crucial to enhance the user experiences in Virtual
Reality (VR). This justifies the sudden burst of novel haptic solutions
proposed these past years in the HCI community. This article is a survey of
Virtual Reality interactions, relying on haptic devices. We propose two
dimensions to describe and compare the current haptic solutions: their degree
of physicality, as well as their degree of actuation. We depict a compromise
between the user and the designer, highlighting how the range of required or
proposed stimulation in VR is opposed to the haptic interfaces flexibility and
their deployment in real-life use-cases. This paper (1) outlines the variety
of haptic solutions and provides a novel perspective for analysing their
associated interactions, (2) highlights the limits of the current evaluation
criteria regarding these interactions, and finally (3) reflects the
interaction, operation and conception potentials of ”encountered-type of
haptic devices”.

haptics, Virtual Reality, human factors, haptic devices

††copyright: acmcopyright††journalyear: 2021††doi:
10.1145/XXXXXXXXX.XXXXXXXX††conference: 32e conférence Francophone sur
l’Interaction Homme-Machine; April 13–16, 2021; Metz, France††booktitle: IHM
’20’21 : 32e conférence Francophone sur l’Interaction Homme-Machine, April
13–16, 2021, Metz, France††price: 15.00††isbn: XXX-X-XXXX-XXXX-X/XX/XX††ccs:
Human-centered computing Virtual reality††ccs: Human-centered computing Haptic
devices††ccs: Human-centered computing Interaction design theory, concepts and
paradigms

Le retour haptique est devenu essentiel pour améliorer l’expérience
utilisateur en Réalité Virtuelle (RV). C’est pourquoi nous observons une
explosion du nombre de solutions haptiques proposées ces dernières années en
IHM. Cet article est une revue de littérature des interactions en RV
s’appuyant sur des dispositifs haptiques. Nous proposons deux dimensions pour
décrire et comparer les solutions haptiques : leur degré de physicalité ainsi
que leur degré de robotisation. Nous formulons un compromis
utilisateur/concepteur, reflétant la variété des stimulations
requises/proposées en RV, en opposition à la flexibilité des interfaces et
leur déploiement en situation réelle. Ce travail (1) offre un panorama des
solutions haptiques en RV ainsi qu’un cadre d’analyse pour étudier les
interactions associées, (2) souligne les limites des critères d’évaluation
actuels pour ce type d’interactions, et finalement (3) reflète les potentiels
interactionnel, opérationnel et conceptuel des interfaces haptiques ”à
contacts intermittents”.

haptique, Réalité Virtuelle, facteurs humains, dispositif haptique

##  1\. Introduction

In the last few years, the terms ”Virtual Reality” and ”Haptics” have been
amongst the most quoted keywords in HCI conferences such as ACM CHI or ACM
UIST. Indeed, Head-Mounted Displays (HMDs) are now affordable and provide high
quality visual and audio feedback, but augmenting the experience by enhancing
VR through the sense of touch (haptic feedback) has become a main challenge. A
large variety of haptic solutions has currently been proposed, nonetheless
they have highly different scopes, due to the wide range of haptic features.
It is hence difficult to compare their similarities and differences and have a
clear understanding of the design possibilities.
In this paper, we present a survey of existing haptic interactions in VR. We
use the terms ”haptic interactions” to emphasize the focus on the users
actions, and to analyse how the ”haptic devices” influence their behaviours in
VR.

We provide a synthesis of existing research on haptic interactions in VR and
depict, from the required haptic features stimulation and interaction
opportunities, a design space discussing and classifying the associated haptic
solutions according to two dimensions: their degree of physicality, i.e. their
physical consistency and level of resemblance as to replicating an object, and
their degree of actuation, i.e. whether they rely on a motor-based hardware
implementation enabling autonomous displacements of the interface (eg changing
its shape or position) (Table 1).
This design space is useful to characterize, classify and compare haptic
interactions and the corresponding haptic solutions. We also propose two
criteria, User experience and Conception costs, highlighting the implicit
trade-offs between the quality of the user experience and the intricacy for
the designer to implement these solutions. Both of the user’s and designer’s
perspectives are hence considered in a novel framework to evaluate haptic
interactions.
Finally, we illustrate the utility of our design space by analyzing and
comparing four haptic solutions. This analysis indicates that (1) the use of
real props in a virtual environment benefits the user experience, but limits
the interactions to the existing props available within the VR arena; (2) the
use of robotised interfaces enables more various interactions; (3) combining
them offers the best user experience/design cost trade-off; (4) current
evaluation methods do not allow a fair representation and comparison of haptic
solutions.

We hence propose guidelines to evaluate haptic interactions from both the user
and designer perspectives. We also outline how intertwining interfaces can
expand haptic opportunities, by conducting a deeper investigation on Robotic
Graphics interfaces (McNeely, 1993) . Indeed, in the quest of the Ultimate
Display (Sutherland, 1965), these show (a) the largest variety of
interactions, (b) the most reliable interfaces through their automation, and
(c) the most natural interactions as they encounter the users at their
positions of interest without further notice.

##  2\. Background

Surveys in Virtual Reality consider the technology itself and its limits
(Zhao, 2009; Zhou and Deng, 2009), or more specifically its use-case
scenarios. VR is indeed used in industries (Berg and Vance, 2017; Zimmermann,
2008), healthcare (Moline, 1997), or in gaming. In gaming, the concerns are
mainly regarding the evaluation protocols (Merino et al., 2020), ie the
presence (Schuemie et al., 2001) and its related questionnaires (Schwind et
al., 2019; Usoh et al., 2000). Surveys for instance compare the results
whenever the questionnaires are asked in VR or in the real world
(Alexandrovsky et al., 2020; Putze et al., 2020). The user behaviour in VR is
also analysed, through gesture recognition (Sagayam and Hemanth, 2017) or
system control techniques (eg menus) (Bowman and Wingrave, 2001).
The research areas are coincidentally almost similar in haptics. Indeed,
surveys analyse haptics themselves (Varalakshmi et al., 2012), haptic devices
(Seifi et al., 2019; Rakkolainen et al., 2020; Talvas et al., 2014; Hayward
and Maclean, 2007) or examine the scenarios which benefit from a stimulation
of the haptic cues. Haptics are used in telemanipulation (Galambos, 2012), for
training in the industry (Xia, 2016; Bloomfield et al., 2003) or for
healthcare purposes (Coles et al., 2011; Rangarajan et al., 2020), or in
gaming (Kim and Schneider, 2020).

Finally, some surveys have been proposed at the intersection of VR and haptics
and focus either on specific methods (pseudo-haptic feedback) (Lécuyer, 2009),
technology according to stimulated haptic features (temperature, shape, skin
stretch, pressure) (Wang et al., 2020d; Dominjon et al., 2007) or the
motivations and applications of each haptic device category (Wang et al.,
2020a). In contrast our survey outlines the variety of haptic interactions and
technologies in VR and provides a framework to analyse them.

##  3\. Scope and Definitions

The scope of this article is to analyse how a single user interacts and is
provided with believable haptic feedback in Virtual Reality (Magnenat-Thalmann
et al., 2005). We thus define the terms ”virtual reality” and ”haptics” and
how they are related.

###  3.1. Virtual Reality

Virtual reality corresponds to a 3D artificial numeric environment in which
users are immersed in. The environment can be projected onto a large screen,
in a simulation platform for instance, or multiple ones, such as with CAVE
technology (where the image is projected onto at least 3 distinct walls of a
room-scale arena). In this survey, we consider an artificial reality
(Wexelblat, 1993) where users do not perceive their physical vicinity: the
outside world is not noticeable and users are fully immersed through a head-
mounted display (HMD). For instance, augmented reality (AR), where the
physical environment is augmented with virtual artefacts, is out of our scope.
Through a Head Mounted Display (HMD), Virtual reality creates immersive
experiences for the users. These are only limited by the designers’
imagination, and are evaluated through presence. Presence is defined as the
”subjective experience of being in one place, even when one is physically
situated in another” (Witmer and Singer, 1998; Slater, 1999). It quantifies
the users’ involvement and naturalness of interactions through control,
sensory, distraction and realism factors. This heavily relies on the sensory
input and output channels, however, as VR was mainly integrating audio and
visual cues, quantifying the haptic contribution in an experience remains
difficult.

###  3.2. Haptics: Tactile vs Kinesthetic Perception

Haptics is the general term for the sense of touch. They are a combination of
two cues: tactile and kinesthetic. The tactile cues are developed through the
skin, while the kinesthetic ones come from proprioception and are through the
muscles and the tendons.

####  3.2.1. Tactile cues:

The skin is composed of four types of mechanoreceptors (Lederman and Klatzky,
2009). The first ones, ”Merkel nerve endings”, transmit mechanical pressure,
position and shapes or edges. They are stimulated whilst reading Braille for
instance. The second ones, ”Ruffini corpuscle end-organ”, are sensitive to
skin stretch and provide both pressure and slippage information. The third
ones are the ”Pacinian corpuscles”, which are sensitive to vibration and
pressure. The last ones, ”Meissner’s corpuscles”, are highly sensitive and
provide light touch and vibrations information. It also contains
thermoreceptors, which transmit information about temperature: the Ruffini
endings respond to warmth, while the Krause ones detect cold. Through tactile
cues, the human can hence feel shapes or edges, pressure, vibrations or
temperature changes.

####  3.2.2. Kinesthetic cues:

The kinesthetic cues rely on proprioception, ie the perception and the
awareness of our own body parts positions and movements. Mechanoreceptors into
the muscles, the ”spindles”, communicate to the nervous system information the
forces muscle generate, as well as their length change (Jones, 2000). The
primary type of spindle is sensitive to the velocity and acceleration of a
muscle contraction or limb movement, while the second type provides
information about static muscle length or limb positions. Kinesthetic cues
hence allow to feel forces, as well as perceiving weights or inertia.

###  3.3. VR & Haptics

Whenever we touch or manipulate an object, the combination of these two
previous cues allows to understand its material, but also its shape and the
constraints it implies to the user. On the one side, adding physical presence
(Lepecq et al., 2008) through haptic feedback in VR enhances the users’
immersion, even at an emotional and physiological scale: the heart rate of a
user can literally increase with the use of haptics through real objects
(Insko, 2001). Haptics are also required for interacting with the environment:
the user needs to control the changes in the environment (Held and Durlach,
1992) and to be aware of the modifications he physically has made (eg moving
virtual objects, pushing a button). On the other side, haptics can benefit
from VR. For instance, Lécuyer et al. leverage the users vision and analyse
how it affects their haptic feedback (Lécuyer, 2009). This approach, ”pseudo-
haptic feedback”, tricks the users’ perception into feeling virtual objects’
stiffness, texture, mass. Many more haptic features can be stimulated, such as
temperature, shape, skin stretch, pressure.

##  4\. Analyzing haptic interactions

The main objective of this survey is to provide analytical tools to evaluate
and compare haptic interactions.

###  4.1. Design space

We propose a two-dimension framework to discuss and classify haptic solutions
in VR (see Table 1).

The first dimension is their degree of physicality, ie how the haptic
perception is tangible/physically consistent/resembling with the virtual
objects. This dimension is drawn as a continuum, from ”no physicality” to
”real objects” (see Figure 2). We find that this continuum can be discretised
as a two-category section: whether they use real objects or not.

The second orthogonal dimension is their degree of actuation, ie whether
haptic solutions rely on a motor-based hardware implementation enabling
autonomous displacements (eg enabling to change its shape, position etc).

###  4.2. Analysis criteria

We consider two main criteria to analyse haptic interactions in VR. They cover
both the user and designer perspectives.

The User experience is the first criterion and includes two aspects:
interaction opportunities and visuo-haptic consistency/discrepancy.
Interaction opportunities represent to which extent haptic solutions allow
users to interact/act (e.g navigate, explore, manipulate) in a VR scene as
opposed as in the real world. Visuo-haptic consistency/discrepancy refers to
the tactile and kinesthetic perceptual rendering of these interactions. These
two sub-criteria are complementary focusing on both action and perception.

The second criterion is the conception cost, i.e. the challenges Designers
should address when designing haptic interactions. We distinguish
implementation and operation costs. Implementation costs include several
technical aspects related to the acceptability of a haptic solution such as
safety, robustness and ease-of-use (Dominjon et al., 2007). Operation costs
include the financial and human costs required to deploy these technologies.

###  4.3. Application

We rely on this design space and criteria to highlight and understand the
trade-offs between the user’s interactions opportunities in VR, and the
designers’ challenges in conception. This survey offers a novel perspective
for researchers to study haptic interactions in VR. It can be used to compare
and analytically evaluate existing haptic interactions. For a given
application, designers can evaluate the most adapted haptic interaction. For a
given technique, they can evaluate a haptic solution depending on their needs
(tasks, workspace, use-cases etc).
.We first discuss haptic interactions from the User perspective (Section 5 \-
Interaction opportunities, Section 6 \- Visuo-Haptic Consistency/Discrepancy).
We then adopt the designer perspective in Section 7. We use our design space
on Sections 6 and 7, which emphasize haptic solutions.

We propose two dimensions to classify current technologies: the degree of
physicality as well as the degree of actuation. Four categories are hence
drawn in this figure: Top Left: No robotics, No real objects; Top Right:
Robotics, No real objects; Bottom Right: Robotics, Real objects; Bottom Left:
No robotics, Real objects. We respectively displayed current technologies and
interaction techniques in the category they belong to.

Table 1. We propose two dimensions to classify current technologies: their
degrees of physicality and actuation.

Figure 1. Tasks in VR: (1) Navigation through Point & Teleport (Funk et al.,
2019); (2) Navigation through a building, using redirection (Cheng, 2019); (3)
Exploration with Bare-Hands: A user finds an invisible haptic code (Bouzbib et
al., 2020); (4) Manipulation: Haptic proxies rearrange themselves to form a
plane the user can manipulate (Zhao et al., 2017); (5) Edition: the user
changes the shape of a haptic 2.5D tabletop (Nakagaki et al., 2016b); (6) The
user is interacted with by a robotic arm to feel emotions (Teyssier et al.,
2020).

##  5\. Interaction Opportunities

In the real world, users move freely without constraints, pick any object of
their environment and then interact with their bare-hands. They also can be
interacted with, from the environment (wind, unexpected obstacles) or from
other users, for instance to catch their attention or to lead them somewhere.
A natural environment also naturally physically constrains users through their
entire body.

In this section, we discuss the interaction opportunities in VR and the
methods available to provide them. In particular, we discuss them through four
main tasks: navigation, exploration, manipulation and edition.

###  5.1. Navigation

We qualify a navigation task as the exploration of the environment through the
vision and the ability to navigate through it via the users displacements. We
identify three main techniques to navigate in VR. The two firsts rely on
controllers and push buttons, where the users do not necessary physically
move. The last one is more natural as it allows the users to walk in the VR
arena.

####  5.1.1. Panning:

With grounded desktop haptic solutions, such as the Virtuose (Haption, 2019),
users need to push a button to clutch the devices and hence move within the
environment.

####  5.1.2. Point & Teleport:

With ungrounded solutions, such as controllers, the common technique is
teleportation. Users point their controllers (Baloup et al., 2018) to
predetermined teleportation target areas, and are displaced in position but
also in orientation (Funk et al., 2019) (Figure 1 \- 1).

####  5.1.3. Real Walking:

Real walking in VR, ”perambulation”, has shown the best immersion and presence
results (Usoh et al., 1999; Steinicke et al., 2013) because it relies on
proprioception and kinesthetic feedback through the legs and gait awareness.
Nonetheless, VR arenas are not infinite and HMD have a limited tracking space,
hence methods need to be developed for the user to be able to move to any
location of interest. One approach is to mount the previously discussed
grounded desktop haptic solutions over mobile (Satler et al., 2011; Lee et
al., 2007; Formaglio et al., 2005; Lee et al., 2009; Nitzsche et al., 2003;
Pavlik et al., 2013) or wearable (Barnaby and Roudaut, 2019) interfaces. Users
however still have to continuously maintain the handle in their palm. Other
interfaces hence allow for free-hands Room-Scale VR (Bouzbib et al., 2020;
Wang et al., 2020c; Yixian et al., 2020). For the users to perambulate in an
infinite workspace, the virtual environment can also visually be warped for
the users to unconsciously modify their trajectory or avoid obstacles (Cheng,
2019; Razzaque et al., 2001; Yang et al., 2019) (Figure 1 \- 2). This infinite
redirection can also be provided from Electro-Muscle Stimulation (EMS) on the
users’ legs (Auda et al., 2019), with wearable electrodes. The user can also
wear actuated stilts to perceive staircases (Schmidt et al., 2015) or a
vibrating shoe to perceive virtual materials (Strohmeier et al., 2020). To
remain unencumbered from these wearable techniques, the VR arena can also
include robotised techniques: users can for instance walk on treadmills
(Vonach et al., 2017; Frissen et al., 2013), or on movable platforms that
encounter their feet (Iwata, 2005, 2013).

###  5.2. Hand Interactions

In the real world, bare-hands interaction is important to execute everyday
tasks (exploration, manipulation, edition). However, in VR, users commonly
have to hold controllers, wearables or handles, which create a discrepancy
between what the users feel and see (Yokokohji et al., 1999). These exploit
the God-object principle (Zilles and Salisbury, 1995), as opposed to bare-
hands Real-touch interactions.

####  5.2.1. God-Object:

The controller is considered as a continuity of the users’ hands, represented
by a proxy that does not undergo physics or rigid collisions, and is attached
to a complementary rigid object with a spring-damper model. This latter hence
moves along with the proxy, but is constrained by the environment. Whenever it
does collide with an object of interest, the users perceive the previous
spring-damper stiffness through kinesthetic feedback.
Users hence interact though a proxy, like a desktop mouse, which position is
not co-located with the users’ vision. Bare-hands interactions are not
necessarily needed depending on the use-cases. For instance, in healthcare and
surgery training, users are more likely to interact with a tool, such as a
scalpel or a clamp. Continuously holding the god-object is hence not a
constrain, however the co-location of vision and haptics is recommended
(Ortega and Coquillart, 2005).

####  5.2.2. Real Touch:

In other scenarios, such as gaming, industry or tool training (Winther et al.,
2020; Strandholt et al., 2020), using the appropriate tools through props and
real objects is more natural. The users however need to be able to reach them
whenever required. Some interfaces (e.g. Robotic Graphics; see Section 7.3)
are hence developed in these regards, to encounter the users whenever they
feel like interacting.

###  5.3. Exploration

As opposed to the previous definition of ”navigation”, based on vision cues,
an ”exploration” task consists in the ability to touch the environment and
understand its constraints. Exploring thoroughly an environment in VR can be
done through different haptic features, and can improve the users depth
perception (Makin et al., 2019) or distances to an object. The different
methods for exploring the environment are detailed in Section 6.
Whenever a user is exploring the environment, shapes or textures are felt
through his body displacements. He needs to move for his skin to stretch
(through tactile cues) or his muscles to contract (through kinesthetic cues).

####  5.3.1. Through Tactile cues:

Whenever real props or material patches are available, users can naturally
interact with their fingertips to feel different materials (Degraen et al.,
2019; Araujo et al., 2016), textures (Benko et al., 2016; Lo et al., 2018),
temperatures (Ziat et al., 2014) or to feel shapes and patterns through their
bare-hands (Bouzbib et al., 2020; Cheng et al., 2017) (Figure 1 \- 3). When no
physicality is available, a stimulation can still be performed. As seen in
Surface haptic displays (Bau et al., 2010), vibrations between 80 to 400 Hz
are felt through the skin, hence users perceive stickiness, smoothness,
pleasure, vibration or friction, and for instance explore a 3D terrain or
volumetric data (Sinclair et al., 2014). Vibrations can then be combined with
auditory and vision cues to render collisions in VR (Boldt et al., 2018).

####  5.3.2. Through Kinesthetic cues:

Exploring the environment can also be done through kinesthetic cues: the users
can literally be physically constrained to feel a wall, using electro-muscle
stimulation (EMS) for instance (Lopes et al., 2017). With the god-object
principle, users can also explore the environments’ constraints through force-
feedback. In this configuration, the users’ arms are constrained by haptic
desktop interfaces, providing strong enough forces to simulate a physical
collision and discriminate shapes.

###  5.4. Manipulation

A manipulation task is performed whenever modifying the position and
orientation of an object.

####  5.4.1. Direct Manipulation:

In VR, we distinguish the direct manipulation (Bryson, 2005), ”the ability for
a user to control objects in a virtual environment in a direct and natural
way, much as objects are manipulated in the real world” from
pointing/selecting an object with controllers. A direct manipulation relies on
the ability to hold an object with kinesthetic feedback, feel its weight
(Lopes et al., 2017; Zenner and Krüger, 2019; Heo et al., 2018; Sagheb et al.,
2019; Zenner and Kruger, 2017; Shigeyama et al., 2019), shape (Follmer et al.,
2013; Sun et al., 2019; Kovacs et al., 2020), and constrains from the virtual
environment, for instance when making objects interact with each other
(Bouzbib et al., 2020). Changing a virtual object position or orientation can
be used as an input in the virtual environment: in (Zhao et al., 2017) for
instance, the user modifies a light intensity by moving a handle prop in the
real environment. By transposing (Lopes et al., 2015) in VR, an object could
even communicate its dynamic use to the user.

####  5.4.2. Pseudo-Haptic Manipulation:

Leveraging vision over haptics allows to move an object with different
friction, weights or force perceptions (Rietzler et al., 2018; Samad et al.,
2019; Pusch and Lécuyer, 2011; Rietzler et al., 2019). For instance, visually
reducing the speed of a virtual prop displacement leads to an increase in the
users’ forces to move it, modifying their friction/weight perceptions.

###  5.5. Edition

We qualify an Edition task as a modification of an object property, other than
its orientation or position (for example through its scale (Xia et al., 2018)
or shape).

####  5.5.1. Physical Edition:

Editing an interface in VR requires it to be fully equipped with sensors. With
wearables for instance, the hand phalanges positions are known, and can be
tightly linked with an object property (Villa Salazar et al., 2020). Knowing
their own position, modular interfaces can be rearranged to provide stretching
or bending tasks (Feick et al., 2020), or be pushed on with a tool to reduce
in size (Teng et al., 2019).
Shape-changing interfaces have been developed to dynamically modify material
properties (Nakagaki et al., 2016b) (Figure 1 \- 5) or augment the
interactions in Augmented Reality (AR) (Leithinger et al., 2013), however
these techniques only consider HMDs and VR as future work directions.
These interfaces are relevant as 2.5D tabletops are already used in VR.
Physically editing the virtual world through them could be implemented in a
near future, by intertwining these interfaces with 3D modelling techniques (De
Araújo et al., 2013).

####  5.5.2. Pseudo-Haptic Edition:

The difficulty behind changing a real object property is to track it in real-
time. This is why pseudo-techniques are relevant: they visually change the
object properties such as their shape (Achibet et al., 2017), compliance (Lee
et al., 2019; Sinclair et al., 2019), or their bending curvature (Heo et al.,
2019) without physically editing the object.

###  5.6. Scenario-based Interactions

In the real world, humans are free to interact with any object without further
notice. In this regard, common controllers enable interactions with any object
through pointing, but they display a high visuo-haptic discrepancy. In more
advanced haptically rendered Virtual environments, users are often constrained
to scenario-based interactions: only a few interactable objects are available,
accordingly with the scenario’s progress.
The greater the virtual:physical haptic consistency, the harder it is to
enhance non-deterministic scenarios, where the user is free to interact with
any object with no regards to the scenario’s progress. High quality haptic
rendering in non-deterministic scenarios can be achieved through three
methods: (a) numerous objects and primitives are available for interactions
(Hettiarachchi and Wigdor, 2016); (b) the users’ intentions are to be
predicted prior to interaction to make it occur (Bouzbib et al., 2020; Cheng
et al., 2017); (c) props modify their own topology to match the users expected
haptic rendering (Siu et al., 2018).

###  5.7. Environment-Initiated Interactions

In both real and virtual environments with tangible interfaces, users usually
are the decision makers and get to choose their points of contact during the
next interaction. However, users themselves can be considered as tangible
interfaces: uncontrolled interactions, such as being touched by a colleague,
or feeling a temperature change in the environment (Shaw et al., 2019; Ziat et
al., 2014), are part of everyday interactions that can be transposed in
Virtual Reality. Replicating a social touch interaction in VR for instance
increases presence (Hoppe et al., 2020) or invokes emotions (Teyssier et al.,
2020).
This type of interactions are recurrent in sports simulations, where the user
is undergoing forces from his environment and perceiving impacts (jumping into
space (Gugenheimer et al., 2016), shooting a soccer ball (Wang et al., 2020b),
goalkeeping in a soccer game (Tsai and Chen, 2019), paragliding (Ye et al.,
2019), intercepting a volleyball (Günther et al., 2020), flying (Cheng et al.,
2014)).
These interactions are involving multiple force types: tension, traction,
reaction, resistance, impact that help enhancing the user experience in VR
(Wang et al., 2020c). These can be strong enough to even lead the user through
forces (Bouzbib et al., 2020).

###  5.8. Whole-Body Involvement

All the previous subsections evoke interactions that mainly involve the hands
or the fingers. This paradigm is revoked in (Zielasko and Riecke, 2020): a
user should be able to choose his posture. This is currently only enabled in
room-scale VR applications, where users experience sitting, standing, climbing
or crouching (Teng et al., 2019; Suzuki et al., 2020; Bouzbib et al., 2020;
Danieau et al., 2012) and interact with their whole-body.

Figure 2. Degree of physicality continuum in VR.(1) Haptic desktop devices
enable to explore the environment through a handle (Lee et al., 2009) with the
god-object principle; (2) A controller (Benko et al., 2016) or (3) a wearable
(Fang et al., 2020) simulate objects for exploration tasks; (4) Mid-air
technology (Rakkolainen et al., 2020) create vibrations through the user’s
hand to simulate an object; (5) Passive proxies are oriented for the user to
feel objects’ primitives with their hands (Cheng et al., 2017); (6) Objects
from the environment are assigned to virtual props with the same primitives
(Hettiarachchi and Wigdor, 2016); (7) Real objects or passive props can be
manipulated and interacted with each other (Bouzbib et al., 2020).

Three physical devices simulating objects are shown with their virtual
counterparts. (1) An inflatable prop in the user’s palm simulates holding a
bomb. (2) A pin-based interface shaped as a ball interacts in the user palm to
replicate a hamster. (3) Different primitives (ball, cube, pyramid) are
displayed on a 2.5D tabletop.

Figure 3. Simulating Objects. (1) A controller with an inflatable prop in the
user’s palm simulates holding a bomb (Teng et al., 2018). (2) A pin-based
interface shaped as a ball interacts in the user palm to replicate a hamster
(Yoshida et al., 2020). (3) Different primitives (ball, cube, pyramid) are
displayed on a 2.5D tabletop (Siu et al., 2018).

##  6\. Visuo-Haptic Consistency/Discrepancy

Visuo-Haptic Consistency is the second aspect of the user experience. We
exploit the dimension degree of physicality of our design space (Table 1) to
discuss the different haptic solutions. In particular, we distinguish whether
these solutions use real objects (exploiting real objects) or not (simulating
objects).

###  6.1. Simulating Objects

Object properties that need to be simulated are their shape, texture,
temperature, weight.

####  6.1.1. No Physicality, (Figure 2 \- 1)

Currently, grounded haptic devices such as the Virtuose (Haption, 2019) or the
PHaNToM (Massie and Salisbury, 1994) simulate objects through their shapes
(Figure 2 \- 1). The rendering is only done through kinesthetic feedback via a
proxy. Conceptually, the ideal link between the users and this proxy is a
massless, infinitely rigid stick, which would be an equivalent to moving the
proxy directly (Hayward and Maclean, 2007; Sato, 2002). These solutions only
provide stimulation at the hand-scale, with no regards to the rest of the
body.

####  6.1.2. Shape Simulation, (Figure 2 \- 2-3-4)

In the same regard, gloves or controllers provide some physicality (Figure 2
\- 2-3). Gloves or exoskeletons literally constrain the users hands for
simulating shapes (Fang et al., 2020; Gu et al., 2016; noa, 2019a; Amirpour et
al., 2019; Choi et al., 2017; Tsai and Rekimoto, 2018; Achibet et al., 2015;
Choi et al., 2016; Nakagaki et al., 2016a; Achibet et al., 2014; Provancher et
al., 2005), or stimulate other haptic features such as stiffness, friction
(Villa Salazar et al., 2020) or slippage (Tsagarakis et al., 2005). These can
be extended to overall body suits for users to feel impacts or even
temperature changes (noa, 2019b; Danieau et al., 2018), or even intertwined
with grounded devices to extend their use-cases (Steed et al., 2020).
Customised controllers are currently designed to be either stimulating the
palm (Sun et al., 2019; Yoshida et al., 2020; de Tinguy et al., 2020) (Figure
3 \- 1, 2), or held in the palm while providing haptic feedback on the
fingertips. For instance, (Whitmire et al., 2018) proposes interchangeable
haptic wheels with different textures or shapes, while (Benko et al., 2016)
enables textures and shapes and (Lee et al., 2019) displays compliance
changes. In these configurations, users hold a single controller, however bi-
manual interactions can be created by combining two controllers. Their link
transmits kinesthetic feedback, and constrain their respective positions to
each other (Strasnick et al., 2018; Wei et al., 2020).
Contactless technology has also been developed for simulating shapes. While
studies demonstrated that interacting with bare-hands increased the user’s
cognitive load (Galais et al., 2019), combining bare-hands interactions with
haptic feedback actually enhances the users involvement. Since haptic feedback
does require contact, ”contactless” technology defines an interaction where
the users are unencumbered, as per Krueger’s postulate (Wexelblat, 1993), and
ultrasounds are sent to their hands, for them to perceive shapes on their
skin, without a physical prop contact (Rakkolainen et al., 2020) (Figure 2 \-
4).
These unencumbered methods are also achieved through shape-changing
interfaces, for instance with balloons arrays (Takizawa et al., 2017) or 2.5D
tabletops (Figure 3 \- 3, Figure 1 \- 5) (Follmer et al., 2013; Siu et al.,
2018; Iwata et al., 2001). These latter are constituted from pins, that raise
and lower themselves to replicate different shapes. In the same regard, swarm
interfaces rearrange themselves to display different shapes. These have mainly
been developed in the real world (Le Goc et al., 2016; Suzuki et al., 2018;
Kim et al., 2020; Suzuki et al., 2019; Ducatelle et al., 2011; Marquardt et
al., 2009) but slowly take off as VR user interfaces (Zhao et al., 2017)
(Figure 1 \- 4). Indeed, while these latter devices are used as desktop
interfaces, the swarm robot idea has extended to the air, with drones for
instance (Gomes et al., 2016; Rubens et al., 2015; Knierim et al., 2017; Hoppe
et al., 2018; Tsykunov and Tsetserukou, 2019).
All of these previous interfaces embrace the Roboxel principle enunciated in
Robotic Graphics (McNeely, 1993): ”cellular robots that dynamically configure
themselves into the desired shape and size”.

####  6.1.3. Object Primitives, (Figure 2 \- 5)

Finally, a user can interact with object primitives. These represent the
simplest geometries available: circle, cube, pyramid, cylinder, torus. Simply
feeling an orientation through the fingertips provides the required
information to understand an object shape, in an exploration task for
instance. Panels with diverse orientations can hence be displayed for a user
to explore various objects in a virtual environment (Cheng et al., 2017)
(Figure 2 \- 5) or directly encounter the user at their position of interest
(Yokokohji et al., 2005; Yokokohji et al., 2001).
On the opposite, a bare-hands manipulation task requires multiple primitives
to be available at the same time within the hand vicinity. This is why the
exploitation of real objects is necessary.

###  6.2. Exploiting Real Objects

Passive haptics (Insko, 2001), ie the use of passive props, consist in placing
real objects corresponding to their exact virtual match at their virtual
position. Insko demonstrated that passive haptics enhanced the virtual
environment (Insko, 2001). Nonetheless, this does suffer from a main
limitation: substituting the physical environment for a virtual one (Simeone
et al., 2015) requires a thorough mapping of objects shapes, sizes, textures,
and requires numerous props (Pair et al., 2003). This can be done with real
objects in simulation rooms for instance (e.g plane cockpit, motorcycle), but
cheaper methods need to be implemented to facilitate their use in other
fields.

####  6.2.1. Object Primitives, (Figure 2 \- 6)

One solution is to extract the primitives of the objects that are already
available in the physical environment, to map virtual objects of the
approximate same primitive over them (Hettiarachchi and Wigdor, 2016) (Figure
2 \- 6).

####  6.2.2. Visuo-Proprioceptive Illusions & Pseudo Haptics

The number of props within the environment can also be reduced, while letting
the users interact at different positions of the physical world. It is
possible to leverage the vision over haptics and modify the users’
proprioception to redirect their trajectory (Kohli, 2010; Kohli et al., 2012,
2013; Azmandian et al., 2016; Gonzalez and Follmer, 2019; Han et al., 2018). A
user might perceive multiple distinct cubes for instance, while interacting
with a single one. On the same principle, the user hand displacement can be
redirected at an angle, up-/down-scaled (Abtahi and Follmer, 2018; Bergström
et al., 2019), or slowed down for friction or weight perception (Samad et al.,
2019; Praveena et al., 2020). These techniques also allow for the exploration
and manipulation of various shapes: models can for instance be added to enable
complex virtual shapes to be mapped over real physical objects boundaries
(Zhao and Follmer, 2018). The user can also be redirected to pinch a multi-
primitive object (cubic, pyramidal and cylindrical) from different locations,
which theoretically widens the variety of available props with a single one
(de Tinguy et al., 2019). On the same principle, pseudo-haptics allow to
modify the users’ shape (Ban et al., 2012a; Ban et al., 2012b) or texture
(Degraen et al., 2019) perceptions when interacting with a physical prop.

####  6.2.3. Displacing Objects, (Figure 2 \- 7)

Whenever objects are indeed available within the environment, various
directions are available to displace them. This displacement allows for
mapping one physical object over multiple ones, but also to display a
multitude of props. These directions embrace the Robotic Shape Display
principle from Robotic Graphics (McNeely, 1993): ”a robot that can reach any
location of a virtual desktop with an end-effector” and matches the user’s
object of interest.
Their usability have been validated through a Wizard-of-Oz implementation,
where human operators move real objects or even people around a Room-scale VR
arena to encounter the users (Cheng et al., 2015) (Figure 4 \- 2). The users
themselves can also reconfigure and actuate real props (Cheng et al., 2018).
Robotic Shape Displays, RSDs, are also called encountered-type of haptic
devices, as they literally encounter the users at their object of interest to
provide haptic feedback. They allow to display real pieces of material (Araujo
et al., 2016; Abtahi et al., 2019), physical props to simulate walls (Bouzbib
et al., 2020; Kim et al., 2018; Yamaguchi et al., 2016), or even display
furniture (Suzuki et al., 2020) or untethered objects (He et al., 2017a, b;
Huang et al., 2020; Bouzbib et al., 2020), that can be interacted with each
other.

Figure 4. Degree of Actuation. (1) No actuation is available. The user’s hand
is redirected to touch a passive prop that cannot move (Azmandian et al.,
2016). The implementation of this technique relies exclusively on a software
development leveraging the vision cues; (2) Human actuators are used to
illustrate the Robotic Graphics (McNeely, 1993) principle with a Wizard of Oz
technique (Cheng et al., 2015). They carry props for the user to feel a real
continuous wall; Encountered-type of haptic devices (3-5): (3) A drone
encounters the users’ hand for exploring passive props; (4) A cartesian robot
displaces itself autonomously for users to interact with physical props
(Bouzbib et al., 2020); (5) A robotic arm with multiple degrees of freedom
displaces itself to encounter the users’ hand, and rotates its shape-
approximation device to provide the right material (Araujo et al., 2016).

##  7\. Conception cost

In practice, designers have to trade-off their interaction design space with
implementation and operational costs in the conception phase. Implementation
costs include technical aspects related to the acceptability of an haptic
solution such as safety, robustness and ease-of-use (Dominjon et al., 2007).
For instance, actuated haptic solutions require a special attention regarding
this criterion. Operation costs include the financial and human cost for using
a haptic solution. The financial cost is measured through the cost of the
haptic device and additional elements such as motion capture systems to
precisely track the users’ hand or the prior preparation of required props.
Human cost refers to both labour time and number of human operators required
during the user’s interactions. For instance, actuated haptic solutions
generally do not require human operators (low human cost) but might be
mechanically expensive.

In this section, we use our two-dimension design space (Table 1) to discuss
haptic solutions according to their conception cost. As non-actuated solutions
globally share the same approaches and have a low implementation cost, we
discuss them together in the ”No Robotics” subsection.

###  7.1. No Robotics

Regarding implementation costs, all non-actuated haptic solutions are safe,
robust and easy-to-use. We depict here an important design choice when opting
for these solutions: either the designer relies on graphics solutions,
leveraging vision cues over haptic ones, or needs operators to displace or
change the interactable props (see Table 1).

####  7.1.1. Passive Props.

Passive props (Insko, 2001) only consist in placing real objects corresponding
to their exact virtual match at their virtual position. They provide a natural
way of interacting through the objects’ natural affordances (Norman, 2013).
They however are limited to the available objects within the scene as they are
not actuated. They only can be used in a scenario-based experience, where the
target is known in advance. The environment hence requires a prop for each
available virtual object.

####  7.1.2. Shape Simulation, Pseudo-Haptics, Visuo-Haptic Illusions, Object
Primitives.

For graphics solutions, users are redirected towards their object of interest
(Azmandian et al., 2016) using visuo-haptic illusions. However, physically
overlaying a prop or primitive over a virtual object has a tracking cost,
which usually relies on trackers which can be operationally costly (eg
Optitrack (Optitrack, 2019) or HTC Trackers).
Otherwise, the users intentions have to be predicted for the interaction to
occur. The users hands are then redirected to the appropriate motionless prop,
for them to explore their object of interest (Cheng et al., 2017).
Operationally, the cost only relies on the proxy fabrication (Figure 2 \- 5).
These implementations offer various scenarios in terms of interaction (even
non-deterministic), at an affordable cost.

####  7.1.3. Surface Haptic Displays.

These techniques exclusively allow for exploration through multiple haptic
features such as friction or textures. They also can integrate a tablet or a
smartphone (Savino, 2020), on which the user can interact at any location.

####  7.1.4. Human Actuators.

This technique consists in using human operators to displace props in the VR
arena. The designers however come across reliability and speed issues with
these operators. Even though they only are used in scenario-based experiences,
delay mechanisms based on graphics need to be implemented (Cheng et al., 2015)
(Figure 4 \- 2) to overcome these issues. Conceptually, they broaden the
interaction scope, however this solution is operationally very costly.

####  7.1.5. Real Props Reassignment.

Instead of using a tracking system for passive props, a depth camera for
instance allows to reassign props to different virtual objects of the same
primitive (Hettiarachchi and Wigdor, 2016) (Figure 2 \- 6). The objects are
hence all available to be interacted with. This drastically reduces the
operational costs as they only rely on computer vision. This enables non-
deterministic scenarios as the real world is literally substituted for a
virtual one (Simeone et al., 2015) and objects can be reassigned with
virtual:physical (He et al., 2017a) mappings.

###  7.2. Robotics & No Real Objects

This section gathers technologies simulating the virtual environment through
actuation: they replicate it to constrain the users.

####  7.2.1. Desktop Haptic Interfaces.

The SPIDAR (Sato, 2002), the Virtuose (Haption, 2019) and other classic
desktop haptic interfaces are already compared in multiple surveys (Dominjon
et al., 2007; Seifi et al., 2019; Wang et al., 2020a) (see Figure 2 \- 1).
They are safe as they are controlled by the user and only constrain their arm
movements with kinesthetic feedback and adapt to any available object from the
virtual scene (non-deterministic scenarios). They show a high perceived
stiffness and robustness, but remain really expensive (¿10k$).

####  7.2.2. Shape-Changing Interfaces, Roboxels, 2.5D Tabletops.

These technologies present a high perceived stiffness and change their shapes
accordingly with the virtual environment (Fitzgerald and Ishii, 2018;
Leithinger et al., 2013). They hence do not require any operator and allow for
non-deterministic scenarios whenever their displacements are enabled (Siu et
al., 2018) (see Figure 3 \- 3). They are however complex to build and require
multiple motors as they are composed of arrays of numerous pins, which define
their haptic fidelity resolution. Even though they present high voltages, they
remain safe around the users. As they require bare-hands interactions, they
hence show a high ease of use.

####  7.2.3. Wearables, Controllers, EMS.

These rely on small torques, which are sufficient to constrain the users body
parts. They are safe and easy to use, but in return are not robust enough to
resist to users’ actions. As they are continuously changing the users’ haptic
perception, they do allow non-deterministic scenarios and change their
rendered stiffness and rigidity as a function of the distance to a virtual
prop (de Tinguy et al., 2020; Kovacs et al., 2020). A customised controller
usually relies on 3D printed parts and small servomotors and can be easily
replicated (Sun et al., 2019) (Figure 2 \- 2,3; Figure 3 \- 1,2).

####  7.2.4. Mid-Air Haptics.

Providing contactless interactions, mid-air haptics also provide a high level
of safety around the user. They however do not allow to navigate the VR
environment, and hence cannot consider non-deterministic scenarios. Their
robustness is very low, as they send ultrasounds to the users and do not
physically constrain them (Rakkolainen et al., 2020).

####  7.2.5. Inflatable Floor.

The floor topology can be modified and inflated to create interactions at the
body-scale (Teng et al., 2019). The users cannot inflate them, however they
can push some tiles down and hence, edit them. These are safe, though they do
not provide a wide range of interactions, but offer multiple static body
postures.

###  7.3. Robotics & Real Objects

In this subsection, we detail the different types of Robotic Shapes Displays -
otherwise known as ”encountered-type of haptic devices”, mentioned in the
Table 1. First, these interfaces move to encounter the users: this feature
optimises their ease of use. Second, as these interfaces move within the user
vicinity, safety concerns are raised in this section, depending on the
interfaces robustness.
Encountered-type of haptic devices combine different types of interaction
techniques: they can provide the users with passive props, textures or
primitives, and allow navigation, exploration, manipulation tasks. Their
mechanical implementations offer a good repeatability and reliability.

####  7.3.1. Cartesian Robot:

In (Bouzbib et al., 2020), CoVR, a physical column mounted over a Cartesian XY
ceiling robot enables interactions at any height and any position of a room-
scale VR arena (see Figure 1 \- 2; Figure 4 \- 4). This implementation
presents a high perceived stiffness, and because it carries passive props
around the arena, enables a high fidelity haptic rendering. It displays high
accuracy and speed, and presents an algorithm which optimises the column’s
displacements as a function of the users intentions. It hence enables non-
deterministic scenarios. Safety measures have been validated in the field. In
practice, the column’s celerity is decreasing around the user, as it is
repulsed by this latter. Its software implementation ensures a safe
environment for the user to perambulate in the arena without unexpected
collision. However, in order to display many props in different scenarios, an
operator is required to create panels and modify them. The materials however
remain cheap, and even though its structure and motors are more expensive than
3D printed cases and servomotors, as per customised controllers for instance,
this solution provides a wide range of interactions.

####  7.3.2. Robotic Arm:

A robotic arm provides more degrees of freedom than the previous Cartesian
robot. This primarily means a higher cost and a higher safety risk. For
instance, H-Wall, using a Kuka LBR Iiwa robot, presents high motor torques and
can hence increase the safety risks around the users. This implementation
hence does not allow non-deterministic scenarios, and presents either a wall
or a revolving door to the user, with a high robustness. Implementations with
smaller torques, such as (Vonach et al., 2017; Araujo et al., 2016) are safer
but display a reduced perceived stiffness. The use-cases for all these
interactions are hence drastically different: H-Wall simulates a rigid wall
while VRRobot (Vonach et al., 2017) and Snake Charmer (Araujo et al., 2016)
(Figure 4 \- 5) present more interaction opportunities. This latter is also
the single Robotic Shape Display that autonomously changes its end-effector,
without an operator.

####  7.3.3. Drones, Swarm Robots, Mobile Platforms:

With drones, the interactions are limited to the available props, for instance
with a single wall at a given position (Yamaguchi et al., 2016). Going from an
active mode (flying) to a passive one (graspable by the user) has a long delay
(10s) (Abtahi et al., 2019), which on top of the safety concerns, does not
allow non-deterministic scenarios. (Tsykunov et al., 2019) however allows the
user to change the drone trajectory to fetch and magnetically recover an
object of interest. Their accuracy and speed are limited (Gomes et al., 2016;
Rubens et al., 2015) compared to the previous grounded interfaces, and can
require dynamic redirection techniques to improve their performances (Abtahi
et al., 2019). As they are ungrounded, they do not have a high robustness nor
perceived stiffness. This is also valid for mobile robots, such as (He et al.,
2017a; Gonzalez et al., 2020), which only display passive props. To decrease
the conception cost, existing vacuuming robots are used as mobile platforms in
(Wang et al., 2020c; Yixian et al., 2020). Designers can choose to duplicate
them, as swarm robots, to enable non-deterministic scenarios (Suzuki et al.,
2020). These are safe to use around the users, as their speed and robustness
are limited. Instead of swarm mobile interfaces, a merry-go-round platform can
also be designed to display various props at an equidistant position from the
user (Huang et al., 2020). All of the previous interfaces require an operator
cost on top of their mechanical and software ones, to modify the interactable
props available, depending on the use-cases.
On the opposite, (Zhao et al., 2017) proposes autonomous reconfigurable
interfaces intertwining both Robotic Shape Displays and Roboxels (McNeely,
1993) principles to get rid of the operator cost (see Figure 1 \- 4). These
small robotic volume elements reconfigure themselves into the users objects of
interest. They have a sufficient perceived stiffness to represent objects, but
are not robust enough to resist to body-scaled forces, for instance to
simulate a rigid wall.

##  8\. Evaluation Protocols

On top of choosing from the different trade-offs between conception and
interaction opportunities, the designer also needs to pick-up an evaluation
protocol. These protocols depend on the VR use-cases. For instance, the haptic
benefits for medical or industrial assembly training can be evaluated against
a real experience condition (Poyade et al., 2012), with criteria such as
completion time, number of errors, user cognitive load (Gutierrez et al.,
2010). On the opposite, the haptic benefits for a gaming experience are more
likely to be evaluated through immersion and presence, comparing ”with/without
haptics” conditions (Cheng et al., 2015). Although some papers do compare
multiple haptic displays (Escobar-Castillejos et al., 2016; Ullrich, 2012), we
point out the lack of referenced evaluation protocols for evaluating haptic
solutions in VR.

###  8.1. Current Reference Evaluation Methods

The most common evaluation methods in VR are the SUS or WS presence
questionnaires (Witmer and Singer, 1998; Slater et al., 1994). These
questionnaires mainly focus on graphics rendering and only two Likert-scale
questions actually focus on haptic feedback: ”How well could you actively
survey the VE using touch?” and ”How well could you manipulate objects in the
VE?”. Besides, most of the above technologies are evaluated against ”no haptic
feedback”, hence the results can seem biased and most of all, expected. This
justifies why some implementations provide results on single parts of the
questionnaire, or arbitrarily combine their results (Choi et al., 2018) with
new subsections (eg ”ability to examine/act”) or tasks specific questions (eg
”How realistic was it to feel different textures?).

Table 2. Comparison & Evaluation of 4 Encountered-type of Haptic Devices,
according to the ”Evaluation section” parameters.

###  8.2. Evaluation Recommendations

Haptics should be more incorporated into the different factors enunciated in
(Witmer and Singer, 1998) (”Control, Sensory, Distraction, Realism”). In this
direction, Kim et al. defined the Haptic Experience model (Kim and Schneider,
2020), where they take into account both of the designer and user experiences.
It depicts how Design parameters (”timeliness, intensity, density and timbre”)
impact Usability requirements (”utility, causality, consistency, saliency”)
and target Experiential dimensions (”harmony, expressivity, autotelics,
immersion, realism”) on the user’s side.
In the same regards, we propose additional guidelines to evaluate haptic
solutions in VR experiments (see Table 2). We believe that the different
elements of interaction opportunities should be added to the users control
parameters.

In the sensory factors, the number of haptic features available should be
added (eg shape, texture, friction, temperature), in line with their quality,
in terms of ”timeliness, intensity, density and timbre”. The usability
requirements should identify the use-cases and number of scenarios with the
proposed solutions. Hence, a good evaluation of the interface timeliness and
usability should anticipate future deployments and avoid unnecessary
developments.

##  9\. Examples: Encountered-Type of Haptic Devices

We propose in this section to compare four encountered-type of haptic devices:
Beyond the Force (BTF) drone (Abtahi et al., 2019) (Figure 4 \- 3), ShapeShift
(Siu et al., 2018) (Figure 3 \- 3), Snake Charmer (Araujo et al., 2016)
(Figure 4 \- 5), and CoVR (Bouzbib et al., 2020) (Figure 4 \- 4).

In terms of interactions and number of props, the drone is the most limited
one. Indeed, because of both safety and implementation limitations, it only
enables free navigation in a reduced workspace. It also allows exploration
(through textures) and manipulation tasks. However, the manipulation task is
at the moment limited to a single light object as BTF cannot handle large
embedded masses yet. Whenever grabbed, it does not provide a haptic
transparency (Hayward and Maclean, 2007) during the interactions because of
its thrust and inertia. For the users to perform different tasks, an operator
needs to manually change the drone configuration. Its mechanical
implementation does not provide a sufficient speed for overlaying virtual
props in non-deterministic scenarios, but its accuracy is also unsatisfactory
and requires dynamic redirection techniques for the interactions to occur. It
also provides unwanted noise and wind, which reduces the interaction realism.
ShapeShift (Siu et al., 2018) is drastically different: it is a 2.5D desktop
interface that displaces itself. Even though a drone is theoretically
available in an infinite workspace, in practice they do share approximately
the same one. As (Siu et al., 2018) relies on a shape-changing interface, no
operator is required and it shape changes itself to overlay the users’ virtual
objects of interest, in non-deterministic scenarios. It allows a free
navigation at a desktop scale, as well as bimanual manipulation and
exploration. Both of these devices haptic transparency are limited as they are
ungrounded solutions. We believe that ShapeShift could be updated to allow
Edition tasks, by synchronising the users force actions with the actuated pins
stiffness. In terms of haptic features, it simulates shapes and stimulates
both tactile and kinesthetic cues. As per all 2.5D tabletops, it can be used
in various applications: 3D terrain exploration, volumetric data etc. Its
resolution seems promising as its studies shows successful object recognition
and haptic search.
The same interactions are available at a desktop scale with Snake Charmer
(Araujo et al., 2016), which provides a wide range of props and stimulation,
as each of its end-effector include 6 faces with various interaction
opportunities (textures to explore, buttons to push, heater and fan to
perceive temperature, handle and lightbulb to grasp and manipulate…). It also
can change its shape approximation device, SAD (ie its end-effector),
autonomously, using magnets. It follows the user hand and orient the expected
interaction face of its SAD prior to the interactions: it hence enables non-
deterministic scenarios. Besides, Snake Charmer has a promising future
regarding its deployment: LobbyBot (noa, [n.d.]), is already in the Renault
industry research lab, to enable VR haptic feedback in the automotive
industry.
Finally, CoVR (Bouzbib et al., 2020) enables the largest workspace as well as
the highest range of interactions. The user is free to navigate in a 30
$m^{3}$ VR arena, and CoVR predicts and physically overlays his object of
interest prior to interaction. These interactions include tactile exploration,
manipulation of untethered objects (full haptic transparency), body postures.
Indeed, CoVR is robust enough to resist body-scaled users, and shows over a
100N perceived stiffness and can carry over 80kg of embedded mass. CoVR can
also initiate the interactions with the users, and is strong enough to lead
the users through forces or even to transport them. Moreover, with the
appropriate physical:virtual mapping (He et al., 2017a), one physical prop can
overlay multiple virtual ones of the same approximate primitive without
redirection techniques. It however requires an operator to create, assemble
and display panels on its sides.

Room-scale VR becomes more and more relevant, and Snake Charmer could benefit
from being attached to an interface such as CoVR. Similarly, intertwining CoVR
with a robotic arm autonomously changing its SAD like Snake Charmer or with a
shape-changing interface could reduce its operational costs. This would
display all of the Robotics Graphics concept capabilities.

##  10\. Conclusion

We analysed in this paper haptic interactions in VR and their corresponding
haptic solutions. We analyzed them from both the user and designer
perspectives by considering interaction opportunities and visuo-haptic
consistency, as well as implementation and operation costs. We proposed a
novel framework to classify haptic displays, through a two-dimension design
space: the interfaces’ degree of physicality and degree of actuation.

We then evaluated these latter solutions from an interaction and conception
perspectives. Implementation-wise, we evaluated the interfaces robustness,
their ease of use as well as their safety considerations. From an operation
perspective, we also evaluated the costs of the proposed solutions.

This survey highlights the variety of props, tasks and haptic features that a
haptic solution can potentially provide in VR. This survey can be used to
analytically evaluate the existing haptic interactions. It can also help VR
designers to choose the desired haptic interaction and/or haptic solution
depending on their needs (tasks, workspace, use-cases etc).

We believe that combining multiple haptic solutions benefits the user
experience, as it optimises the above criteria. Encountered-type of haptic
interfaces were then highlighted as they already combine multiple interaction
techniques: they displace passive props in potentially large VR arenas and
allow for numerous tasks, such as navigation, exploration, manipulation, and
even allow the user to be interacted with.

## References

  * (1)
  * noa ([n.d.]) [n.d.].  renault.  https://www.clarte-lab.fr/component/tags/tag/renault
  * noa (2019a) 2019a.  CyberGrasp.  http://www.cyberglovesystems.com/cybergrasp
  * noa (2019b) 2019b.  Teslasuit | Full body haptic VR suit for motion capture and training.  https://teslasuit.io/
  * Abtahi and Follmer (2018) Parastoo Abtahi and Sean Follmer. 2018.  Visuo-Haptic Illusions for Improving the Perceived Performance of Shape Displays. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–13.  https://doi.org/10.1145/3173574.3173724
  * Abtahi et al. (2019) Parastoo Abtahi, Benoit Landry, Jackie (Junrui) Yang, Marco Pavone, Sean Follmer, and James A. Landay. 2019.  Beyond The Force: Using Quadcopters to Appropriate Objects and the Environment for Haptics in Virtual Reality. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–13.  https://doi.org/10.1145/3290605.3300589
  * Achibet et al. (2015) Merwan Achibet, Adrien Girard, Anthony Talvas, Maud Marchal, and Anatole Lecuyer. 2015.  Elastic-Arm: Human-scale passive haptic feedback for augmenting interaction and perception in virtual environments. In _2015 IEEE Virtual Reality (VR)_. IEEE, Arles, Camargue, Provence, France, 63–68.  https://doi.org/10.1109/VR.2015.7223325
  * Achibet et al. (2017) Merwan Achibet, Benoit Le Gouis, Maud Marchal, Pierre-Alexandre Leziart, Ferran Argelaguet, Adrien Girard, Anatole Lecuyer, and Hiroyuki Kajimoto. 2017.  FlexiFingers: Multi-finger interaction in VR combining passive haptics and pseudo-haptics. In _2017 IEEE Symposium on 3D User Interfaces (3DUI)_. IEEE, Los Angeles, CA, USA, 103–106.  https://doi.org/10.1109/3DUI.2017.7893325
  * Achibet et al. (2014) Merwan Achibet, Maud Marchal, Ferran Argelaguet, and Anatole Lecuyer. 2014.  The Virtual Mitten: A novel interaction paradigm for visuo-haptic manipulation of objects using grip force. In _2014 IEEE Symposium on 3D User Interfaces (3DUI)_. IEEE, MN, USA, 59–66.  https://doi.org/10.1109/3DUI.2014.6798843
  * Alexandrovsky et al. (2020) Dmitry Alexandrovsky, Susanne Putze, Michael Bonfert, Sebastian Höffner, Pitt Michelmann, Dirk Wenig, Rainer Malaka, and Jan David Smeddinck. 2020.  Examining Design Choices of Questionnaires in VR User Studies. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–21.  https://doi.org/10.1145/3313831.3376260
  * Amirpour et al. (2019) E. Amirpour, M. Savabi, A. Saboukhi, M. Rahimi Gorii, H. Ghafarirad, R. Fesharakifard, and S. Mehdi Rezaei. 2019.  Design and Optimization of a Multi-DOF Hand Exoskeleton for Haptic Applications. In _2019 7th International Conference on Robotics and Mechatronics (ICRoM)_. 270–275.  https://doi.org/10.1109/ICRoM48714.2019.9071884 ISSN: 2572-6889.
  * Araujo et al. (2016) Bruno Araujo, Ricardo Jota, Varun Perumal, Jia Xian Yao, Karan Singh, and Daniel Wigdor. 2016\.  Snake Charmer: Physically Enabling Virtual Objects. In _Proceedings of the TEI ’16: Tenth International Conference on Tangible, Embedded, and Embodied Interaction - TEI ’16_. ACM Press, Eindhoven, Netherlands, 218–226.  https://doi.org/10.1145/2839462.2839484
  * Auda et al. (2019) Jonas Auda, Max Pascher, and Stefan Schneegass. 2019.  Around the (Virtual) World: Infinite Walking in Virtual Reality Using Electrical Muscle Stimulation. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–8.  https://doi.org/10.1145/3290605.3300661
  * Azmandian et al. (2016) Mahdi Azmandian, Mark Hancock, Hrvoje Benko, Eyal Ofek, and Andrew D. Wilson. 2016.  Haptic Retargeting: Dynamic Repurposing of Passive Haptics for Enhanced Virtual Reality Experiences. In _Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI ’16_. ACM Press, Santa Clara, California, USA, 1968–1979.  https://doi.org/10.1145/2858036.2858226
  * Baloup et al. (2018) Marc Baloup, Veïs Oudjail, Thomas Pietrzak, and Géry Casiez. 2018.  Pointing techniques for distant targets in virtual reality. In _Proceedings of the 30th Conference on l’Interaction Homme-Machine - IHM ’18_. ACM Press, Brest, France, 100–107.  https://doi.org/10.1145/3286689.3286696
  * Ban et al. (2012a) Y. Ban, T. Kajinami, T. Narumi, T. Tanikawa, and M. Hirose. 2012a.  Modifying an identified curved surface shape using pseudo-haptic effect. In _2012 IEEE Haptics Symposium (HAPTICS)_. 211–216.  https://doi.org/10.1109/HAPTIC.2012.6183793
  * Ban et al. (2012b) Yuki Ban, Takuji Narumi, Tomohiro Tanikawa, and Michitaka Hirose. 2012b.  Modifying an identified position of edged shapes using pseudo-haptic effects. In _Proceedings of the 18th ACM symposium on Virtual reality software and technology - VRST ’12_. ACM Press, Toronto, Ontario, Canada, 93.  https://doi.org/10.1145/2407336.2407353
  * Barnaby and Roudaut (2019) Gareth Barnaby and Anne Roudaut. 2019.  Mantis: A Scalable, Lightweight and Accessible Architecture to Build Multiform Force Feedback Systems. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 937–948.  https://doi.org/10.1145/3332165.3347909
  * Bau et al. (2010) Olivier Bau, Ivan Poupyrev, Ali Israr, and Chris Harrison. 2010.  TeslaTouch: electrovibration for touch surfaces. In _Proceedings of the 23nd annual ACM symposium on User interface software and technology - UIST ’10_. ACM Press, New York, New York, USA, 283\.  https://doi.org/10.1145/1866029.1866074
  * Benko et al. (2016) Hrvoje Benko, Christian Holz, Mike Sinclair, and Eyal Ofek. 2016\.  NormalTouch and TextureTouch: High-fidelity 3D Haptic Shape Rendering on Handheld Virtual Reality Controllers. In _Proceedings of the 29th Annual Symposium on User Interface Software and Technology - UIST ’16_. ACM Press, Tokyo, Japan, 717–728.  https://doi.org/10.1145/2984511.2984526
  * Berg and Vance (2017) Leif P. Berg and Judy M. Vance. 2017.  Industry use of virtual reality in product design and manufacturing: a survey.  _Virtual Reality_ 21, 1 (March 2017), 1–17.  https://doi.org/10.1007/s10055-016-0293-9
  * Bergström et al. (2019) Joanna Bergström, Aske Mottelson, and Jarrod Knibbe. 2019\.  Resized Grasping in VR: Estimating Thresholds for Object Discrimination. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology_. ACM, New Orleans LA USA, 1175–1183.  https://doi.org/10.1145/3332165.3347939
  * Bloomfield et al. (2003) A. Bloomfield, Yu Deng, J. Wampler, P. Rondot, D. Harth, M. McManus, and N. Badler. 2003.  A taxonomy and comparison of haptic actions for disassembly tasks. In _IEEE Virtual Reality, 2003\. Proceedings._ IEEE Comput. Soc, Los Angeles, CA, USA, 225–231.  https://doi.org/10.1109/VR.2003.1191143
  * Boldt et al. (2018) Mette Boldt, Boxuan Liu, Tram Nguyen, Alina Panova, Ramneek Singh, Alexander Steenbergen, Rainer Malaka, Jan Smeddinck, Michael Bonfert, Inga Lehne, Melina Cahnbley, Kim Korschinq, Loannis Bikas, Stefan Finke, Martin Hanci, and Valentin Kraft. 2018\.  You Shall Not Pass: Non-Intrusive Feedback for Virtual Walls in VR Environments with Room-Scale Mapping. In _2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)_. IEEE, Reutlingen, 143–150.  https://doi.org/10.1109/VR.2018.8446177
  * Bouzbib et al. (2020) Elodie Bouzbib, Gilles Bailly, Sinan Haliyo, and Pascal Frey. 2020.  CoVR: A Large-Scale Force-Feedback Robotic Interface for Non-Deterministic Scenarios in VR. In _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_. ACM, Virtual Event USA, 209–222.  https://doi.org/10.1145/3379337.3415891
  * Bowman and Wingrave (2001) D.A. Bowman and C.A. Wingrave. 2001.  Design and evaluation of menu systems for immersive virtual environments. In _Proceedings IEEE Virtual Reality 2001_. IEEE Comput. Soc, Yokohama, Japan, 149–156.  https://doi.org/10.1109/VR.2001.913781
  * Bryson (2005) Steve Bryson. 2005\.  Direct Manipulation in Virtual Reality.  In _Visualization Handbook_. Elsevier, 413–430.  https://doi.org/10.1016/B978-012387582-2/50023-X
  * Cheng (2019) Lung-Pan Cheng. 2019\.  VRoamer: Generating On-The-Fly VR Experiences While Walking inside Large, Unknown Real-World Building Environments.  (2019), 8.
  * Cheng et al. (2018) Lung-Pan Cheng, Li Chang, Sebastian Marwecki, and Patrick Baudisch. 2018.  iTurk: Turning Passive Haptics into Active Haptics by Making Users Reconfigure Props in Virtual Reality. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–10.  https://doi.org/10.1145/3173574.3173663
  * Cheng et al. (2014) Lung-Pan Cheng, Patrick Lühne, Pedro Lopes, Christoph Sterz, and Patrick Baudisch. 2014.  Haptic Turk: a Motion Platform Based on People.  (2014), 11.
  * Cheng et al. (2017) Lung-Pan Cheng, Eyal Ofek, Christian Holz, Hrvoje Benko, and Andrew D. Wilson. 2017.  Sparse Haptic Proxy: Touch Feedback in Virtual Environments Using a General Passive Prop. In _Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17_. ACM Press, Denver, Colorado, USA, 3718–3728.  https://doi.org/10.1145/3025453.3025753
  * Cheng et al. (2015) Lung-Pan Cheng, Thijs Roumen, Hannes Rantzsch, Sven Köhler, Patrick Schmidt, Robert Kovacs, Johannes Jasper, Jonas Kemper, and Patrick Baudisch. 2015.  TurkDeck: Physical Virtual Reality Based on People. In _Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology - UIST ’15_. ACM Press, Daegu, Kyungpook, Republic of Korea, 417–426.  https://doi.org/10.1145/2807442.2807463
  * Choi et al. (2017) Inrak Choi, Heather Culbertson, Mark R. Miller, Alex Olwal, and Sean Follmer. 2017.  Grabity: A Wearable Haptic Interface for Simulating Weight and Grasping in Virtual Reality. In _Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology - UIST ’17_. ACM Press, Québec City, QC, Canada, 119–130.  https://doi.org/10.1145/3126594.3126599
  * Choi et al. (2016) Inrak Choi, Elliot W. Hawkes, David L. Christensen, Christopher J. Ploch, and Sean Follmer. 2016.  Wolverine: A wearable haptic interface for grasping in virtual reality. In _2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)_. IEEE, Daejeon, South Korea, 986–993.  https://doi.org/10.1109/IROS.2016.7759169
  * Choi et al. (2018) Inrak Choi, Eyal Ofek, Hrvoje Benko, Mike Sinclair, and Christian Holz. 2018.  CLAW: A Multifunctional Handheld Haptic Controller for Grasping, Touching, and Triggering in Virtual Reality. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–13.  https://doi.org/10.1145/3173574.3174228
  * Coles et al. (2011) Timothy R. Coles, Dwight Meglan, and Nigel W. John. 2011\.  The Role of Haptics in Medical Training Simulators: A Survey of the State of the Art.  _IEEE Transactions on Haptics_ 4, 1 (Jan. 2011), 51–66.  https://doi.org/10.1109/TOH.2010.19
  * Danieau et al. (2012) Fabien Danieau, Julien Fleureau, Philippe Guillotel, Nicolas Mollet, Anatole Lécuyer, and Marc Christie. 2012.  HapSeat: producing motion sensation with multiple force-feedback devices embedded in a seat. In _Proceedings of the 18th ACM symposium on Virtual reality software and technology - VRST ’12_. ACM Press, Toronto, Ontario, Canada, 69\.  https://doi.org/10.1145/2407336.2407350
  * Danieau et al. (2018) Fabien Danieau, Philippe Guillotel, Olivier Dumas, Thomas Lopez, Bertrand Leroy, and Nicolas Mollet. 2018\.  HFX studio: haptic editor for full-body immersive experiences. In _Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology - VRST ’18_. ACM Press, Tokyo, Japan, 1–9.  https://doi.org/10.1145/3281505.3281518
  * De Araújo et al. (2013) Bruno R. De Araújo, Géry Casiez, Joaquim A. Jorge, and Martin Hachet. 2013.  Mockup Builder: 3D modeling on and above the surface.  _Computers & Graphics_ 37, 3 (May 2013), 165–178.  https://doi.org/10.1016/j.cag.2012.12.005
  * de Tinguy et al. (2020) Xavier de Tinguy, Thomas Howard, Claudio Pacchierotti, Maud Marchal, and Anatole Lécuyer. 2020\.  WeATaViX: WEarable Actuated TAngibles for VIrtual reality eXperiences.  (2020), 9.
  * de Tinguy et al. (2019) Xavier de Tinguy, Claudio Pacchierotti, Maud Marchal, and Anatole Lecuyer. 2019.  Toward Universal Tangible Objects: Optimizing Haptic Pinching Sensations in 3D Interaction. In _2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)_. IEEE, Osaka, Japan, 321–330.  https://doi.org/10.1109/VR.2019.8798205
  * Degraen et al. (2019) Donald Degraen, André Zenner, and Antonio Krüger. 2019\.  Enhancing Texture Perception in Virtual Reality Using 3D-Printed Hair Structures. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–12.  https://doi.org/10.1145/3290605.3300479
  * Dominjon et al. (2007) Lionel Dominjon, Jérôme Perret, and Anatole Lécuyer. 2007\.  Novel devices and interaction techniques for human-scale haptics.  _The Visual Computer_ 23, 4 (March 2007), 257–266.  https://doi.org/10.1007/s00371-007-0100-4
  * Ducatelle et al. (2011) Frederick Ducatelle, Gianni A. Di Caro, Carlo Pinciroli, and Luca M. Gambardella. 2011\.  Self-organized cooperation between robotic swarms.  _Swarm Intelligence_ 5, 2 (June 2011), 73–96.  https://doi.org/10.1007/s11721-011-0053-0
  * Escobar-Castillejos et al. (2016) David Escobar-Castillejos, Julieta Noguez, Luis Neri, Alejandra Magana, and Bedrich Benes. 2016\.  A Review of Simulators with Haptic Devices for Medical Training.  _Journal of Medical Systems_ 40, 4 (April 2016), 1–22.  https://doi.org/10.1007/s10916-016-0459-8
  * Fang et al. (2020) Cathy Fang, Yang Zhang, Matthew Dworman, and Chris Harrison. 2020\.  Wireality: Enabling Complex Tangible Geometries in Virtual Reality with Worn Multi-String Haptics.  (2020), 10.
  * Feick et al. (2020) Martin Feick, Scott Bateman, Anthony Tang, André Miede, and Nicolai Marquardt. 2020.  TanGi: Tangible Proxies for Embodied Object Exploration and Manipulation in Virtual Reality.  _arXiv:2001.03021 [cs]_ (Jan. 2020).  http://arxiv.org/abs/2001.03021 arXiv: 2001.03021.
  * Fitzgerald and Ishii (2018) Daniel Fitzgerald and Hiroshi Ishii. 2018.  Mediate: A Spatial Tangible Interface for Mixed Reality. In _Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems_. ACM, Montreal QC Canada, 1–6.  https://doi.org/10.1145/3170427.3188472
  * Follmer et al. (2013) Sean Follmer, Daniel Leithinger, Alex Olwal, Akimitsu Hogge, and Hiroshi Ishii. 2013.  inFORM: dynamic physical affordances and constraints through shape and object actuation. In _Proceedings of the 26th annual ACM symposium on User interface software and technology - UIST ’13_. ACM Press, St. Andrews, Scotland, United Kingdom, 417–426.  https://doi.org/10.1145/2501988.2502032
  * Formaglio et al. (2005) A. Formaglio, A. Giannitrapani, M. Franzini, D. Prattichizzo, and F. Barbagli. 2005\.  Performance of Mobile Haptic Interfaces. In _Proceedings of the 44th IEEE Conference on Decision and Control_. 8343–8348.  https://doi.org/10.1109/CDC.2005.1583513
  * Frissen et al. (2013) Ilja Frissen, Jennifer L. Campos, Manish Sreenivasa, and Marc O. Ernst. 2013.  Enabling Unconstrained Omnidirectional Walking Through Virtual Environments: An Overview of the CyberWalk Project.  In _Human Walking in Virtual Environments: Perception, Technology, and Applications_ , Frank Steinicke, Yon Visell, Jennifer Campos, and Anatole Lécuyer (Eds.). Springer, New York, NY, 113–144.  https://doi.org/10.1007/978-1-4419-8432-6_6
  * Funk et al. (2019) Markus Funk, Florian Müller, Marco Fendrich, Megan Shene, Moritz Kolvenbach, Niclas Dobbertin, Sebastian Günther, and Max Mühlhäuser. 2019.  Assessing the Accuracy of Point & Teleport Locomotion with Orientation Indication for Virtual Reality using Curved Trajectories. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–12.  https://doi.org/10.1145/3290605.3300377
  * Galais et al. (2019) Thomas Galais, Alexandra Delmas, and Rémy Alonso. 2019\.  Natural interaction in virtual reality: impact on the cognitive load. In _Proceedings of the 31st Conference on l’Interaction Homme-Machine Adjunct - IHM ’19_. ACM Press, Grenoble, France, 1–9.  https://doi.org/10.1145/3366551.3370342
  * Galambos (2012) Péter Galambos. 2012\.  Vibrotactile Feedback for Haptics and Telemanipulation: Survey, Concept and Experiment.  _Acta Polytechnica Hungarica_ 9, 1 (2012), 25\.
  * Gomes et al. (2016) Antonio Gomes, Calvin Rubens, Sean Braley, and Roel Vertegaal. 2016.  BitDrones: Towards Using 3D Nanocopter Displays as Interactive Self-Levitating Programmable Matter. In _Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI ’16_. ACM Press, Santa Clara, California, USA, 770–780.  https://doi.org/10.1145/2858036.2858519
  * Gonzalez et al. (2020) Eric J. Gonzalez, Parastoo Abtahi, and Sean Follmer. 2020\.  REACH+: Extending the Reachability of Encountered-type Haptics Devices through Dynamic Redirection in VR. In _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_. ACM, Virtual Event USA, 236–248.  https://doi.org/10.1145/3379337.3415870
  * Gonzalez and Follmer (2019) Eric J. Gonzalez and Sean Follmer. 2019.  Investigating the Detection of Bimanual Haptic Retargeting in Virtual Reality. In _25th ACM Symposium on Virtual Reality Software and Technology on - VRST ’19_. ACM Press, Parramatta, NSW, Australia, 1–5.  https://doi.org/10.1145/3359996.3364248
  * Gu et al. (2016) Xiaochi Gu, Yifei Zhang, Weize Sun, Yuanzhe Bian, Dao Zhou, and Per Ola Kristensson. 2016\.  Dexmo: An Inexpensive and Lightweight Mechanical Exoskeleton for Motion Capture and Force Feedback in VR. In _Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI ’16_. ACM Press, Santa Clara, California, USA, 1991–1995.  https://doi.org/10.1145/2858036.2858487
  * Gugenheimer et al. (2016) Jan Gugenheimer, Dennis Wolf, Eythor R. Eiriksson, Pattie Maes, and Enrico Rukzio. 2016.  GyroVR: Simulating Inertia in Virtual Reality using Head Worn Flywheels. In _Proceedings of the 29th Annual Symposium on User Interface Software and Technology_. ACM, Tokyo Japan, 227–232.  https://doi.org/10.1145/2984511.2984535
  * Gutierrez et al. (2010) T. Gutierrez, J. Rodriguez, Y. Velaz, S. Casado, A. Suescun, and E. J. Sanchez. 2010\.  IMA-VR: A multimodal virtual training system for skills transfer in Industrial Maintenance and Assembly tasks.  _19th International Symposium in Robot and Human Interactive Communication_ (2010).  https://www.academia.edu/15623406/IMA_VR_A_multimodal_virtual_training_system_for_skills_transfer_in_Industrial_Maintenance_and_Assembly_tasks
  * Günther et al. (2020) Sebastian Günther, Dominik Schön, Florian Müller, Max Mühlhäuser, and Martin Schmitz. 2020\.  PneumoVolley: Pressure-based Haptic Feedback on the Head through Pneumatic Actuation.  (2020), 10.
  * Han et al. (2018) Dustin T. Han, Mohamed Suhail, and Eric D. Ragan. 2018\.  Evaluating Remapped Physical Reach for Hand Interactions with Passive Haptics in Virtual Reality.  _IEEE Transactions on Visualization and Computer Graphics_ 24, 4 (April 2018), 1467–1476.  https://doi.org/10.1109/TVCG.2018.2794659
  * Haption (2019) Haption. 2019.  Virtuose™ 6D - HAPTION SA.  https://www.haption.com/en/products-en/virtuose-6d-en.html
  * Hayward and Maclean (2007) Vincent Hayward and Karon Maclean. 2007.  Do it yourself haptics: part I.  _IEEE Robotics & Automation Magazine_ 14, 4 (Dec. 2007), 88–104.  https://doi.org/10.1109/M-RA.2007.907921
  * He et al. (2017b) Zhenyi He, Fengyuan Zhu, Aaron Gaudette, and Ken Perlin. 2017b.  Robotic Haptic Proxies for Collaborative Virtual Reality.  _arXiv:1701.08879 [cs]_ (Jan. 2017).  http://arxiv.org/abs/1701.08879 arXiv: 1701.08879.
  * He et al. (2017a) Zhenyi He, Fengyuan Zhu, and Ken Perlin. 2017a.  PhyShare: Sharing Physical Interaction in Virtual Reality.  _arXiv:1708.04139 [cs]_ (Aug. 2017).  http://arxiv.org/abs/1708.04139 arXiv: 1708.04139.
  * Held and Durlach (1992) Richard M. Held and Nathaniel I. Durlach. 1992.  Telepresence.  _Presence: Teleoperators and Virtual Environments_ 1, 1 (Jan. 1992), 109–112.  https://doi.org/10.1162/pres.1992.1.1.109
  * Heo et al. (2018) Seongkook Heo, Christina Chung, Geehyuk Lee, and Daniel Wigdor. 2018.  Thor’s Hammer: An Ungrounded Force Feedback Device Utilizing Propeller-Induced Propulsive Force. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–11.  https://doi.org/10.1145/3173574.3174099
  * Heo et al. (2019) Seongkook Heo, Jaeyeon Lee, and Daniel Wigdor. 2019\.  PseudoBend: Producing Haptic Illusions of Stretching, Bending, and Twisting Using Grain Vibrations. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 803–813.  https://doi.org/10.1145/3332165.3347941
  * Hettiarachchi and Wigdor (2016) Anuruddha Hettiarachchi and Daniel Wigdor. 2016.  Annexing Reality: Enabling Opportunistic Use of Everyday Objects as Tangible Proxies in Augmented Reality. In _Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI ’16_. ACM Press, Santa Clara, California, USA, 1957–1967.  https://doi.org/10.1145/2858036.2858134
  * Hoppe et al. (2018) Matthias Hoppe, Pascal Knierim, Thomas Kosch, Markus Funk, Lauren Futami, Stefan Schneegass, Niels Henze, Albrecht Schmidt, and Tonja Machulla. 2018.  VRHapticDrones: Providing Haptics in Virtual Reality through Quadcopters. In _Proceedings of the 17th International Conference on Mobile and Ubiquitous Multimedia - MUM 2018_. ACM Press, Cairo, Egypt, 7–18.  https://doi.org/10.1145/3282894.3282898
  * Hoppe et al. (2020) Matthias Hoppe, Daniel Neumann, Stephan Streuber, Albrecht Schmidt, and Tonja-Katrin Machulla. 2020\.  _A Human Touch: Social Touch Increases the Perceived Human-likeness of Agents in Virtual Reality_.  https://doi.org/10.1145/3313831.3376719
  * Huang et al. (2020) Hsin-Yu Huang, Chih-Wei Ning, Po-Yao Wang, Jen-Hao Cheng, and Lung-Pan Cheng. 2020.  Haptic-go-round: A Surrounding Platform for Encounter-type Haptics in Virtual Reality Experiences. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–10.  https://doi.org/10.1145/3313831.3376476
  * Insko (2001) Brent Edward Insko. 2001\.  Passive Haptics Significantly Enhances Virtual Environments.  (2001), 111.
  * Iwata (2005) Hiroo Iwata. 2005\.  CirculaFloor.  https://ieeexplore.ieee.org/abstract/document/1381227
  * Iwata (2013) Hiroo Iwata. 2013\.  Locomotion Interfaces.  In _Human Walking in Virtual Environments: Perception, Technology, and Applications_ , Frank Steinicke, Yon Visell, Jennifer Campos, and Anatole Lécuyer (Eds.). Springer, New York, NY, 199–219.  https://doi.org/10.1007/978-1-4419-8432-6_9
  * Iwata et al. (2001) Hiroo Iwata, Hiroaki Yano, Fumitaka Nakaizumi, and Ryo Kawamura. 2001.  Project FEELEX: adding haptic surface to graphics. In _Proceedings of the 28th annual conference on Computer graphics and interactive techniques - SIGGRAPH ’01_. ACM Press, Not Known, 469–476.  https://doi.org/10.1145/383259.383314
  * Jones (2000) Lynette Jones. 2000\.  Kinesthetic Sensing.  _Human and Machine Haptics_ (2000).  http://bdml.stanford.edu/twiki/pub/Haptics/PapersInProgress/jones00.pdf
  * Kim and Schneider (2020) Erin Kim and Oliver Schneider. 2020.  Defining Haptic Experience: Foundations for Understanding, Communicating, and Evaluating HX. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–13.  https://doi.org/10.1145/3313831.3376280
  * Kim et al. (2020) Lawrence H. Kim, Daniel S. Drew, Veronika Domova, and Sean Follmer. 2020.  User-defined Swarm Robot Control. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–13.  https://doi.org/10.1145/3313831.3376814
  * Kim et al. (2018) Yaesol Kim, Hyun Jung Kim, and Young J. Kim. 2018.  Encountered-type haptic display for large VR environment using per-plane reachability maps: Encountered-type Haptic Display for Large VR Environment.  _Computer Animation and Virtual Worlds_ 29, 3-4 (May 2018), e1814.  https://doi.org/10.1002/cav.1814
  * Knierim et al. (2017) Pascal Knierim, Thomas Kosch, Valentin Schwind, Markus Funk, Francisco Kiss, Stefan Schneegass, and Niels Henze. 2017.  Tactile Drones - Providing Immersive Tactile Feedback in Virtual Reality through Quadcopters. In _Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems - CHI EA ’17_. ACM Press, Denver, Colorado, USA, 433–436.  https://doi.org/10.1145/3027063.3050426
  * Kohli (2010) Luv Kohli. 2010\.  Redirected touching: Warping space to remap passive haptics. In _2010 IEEE Symposium on 3D User Interfaces (3DUI)_. IEEE, Waltham, MA, USA, 129–130.  https://doi.org/10.1109/3DUI.2010.5444703
  * Kohli et al. (2012) L. Kohli, M. C. Whitton, and F. P. Brooks. 2012.  Redirected touching: The effect of warping space on task performance. In _2012 IEEE Symposium on 3D User Interfaces (3DUI)_. IEEE, Costa Mesa, CA, 105–112.  https://doi.org/10.1109/3DUI.2012.6184193
  * Kohli et al. (2013) Luv Kohli, Mary C. Whitton, and Frederick P. Brooks. 2013\.  Redirected Touching: Training and adaptation in warped virtual spaces. In _2013 IEEE Symposium on 3D User Interfaces (3DUI)_. IEEE, Orlando, FL, 79–86.  https://doi.org/10.1109/3DUI.2013.6550201
  * Kovacs et al. (2020) Robert Kovacs, Eyal Ofek, Mar Gonzalez Franco, Alexa Fay Siu, Sebastian Marwecki, Christian Holz, and Mike Sinclair. 2020.  Haptic PIVOT: On-Demand Handhelds in VR. In _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_ _(UIST ’20)_. Association for Computing Machinery, New York, NY, USA, 1046–1059.  https://doi.org/10.1145/3379337.3415854
  * Le Goc et al. (2016) Mathieu Le Goc, Lawrence H. Kim, Ali Parsaei, Jean-Daniel Fekete, Pierre Dragicevic, and Sean Follmer. 2016.  Zooids: Building Blocks for Swarm User Interfaces. In _Proceedings of the 29th Annual Symposium on User Interface Software and Technology - UIST ’16_. ACM Press, Tokyo, Japan, 97–109.  https://doi.org/10.1145/2984511.2984547
  * Lederman and Klatzky (2009) S. J. Lederman and R. L. Klatzky. 2009.  Haptic perception: A tutorial.  _Attention, Perception & Psychophysics_ 71, 7 (Oct. 2009), 1439–1459.  https://doi.org/10.3758/APP.71.7.1439
  * Lee et al. (2007) Chaehyun Lee, Min Sik Hong, In Lee, Oh Kyu Choi, Kyung-Lyong Han, Yoo Yeon Kim, Seungmoon Choi, and Jin S Lee. 2007\.  Mobile Haptic Interface for Large Immersive Virtual Environments: PoMHI v0.5.  (2007), 2.
  * Lee et al. (2009) In Lee, Inwook Hwang, Kyung-Lyoung Han, Oh Kyu Choi, Seungmoon Choi, and Jin S. Lee. 2009\.  System improvements in Mobile Haptic Interface. In _World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems_. IEEE, Salt Lake City, UT, USA, 109–114.  https://doi.org/10.1109/WHC.2009.4810834
  * Lee et al. (2019) Jaeyeon Lee, Mike Sinclair, Mar Gonzalez-Franco, Eyal Ofek, and Christian Holz. 2019\.  TORC: A Virtual Reality Controller for In-Hand High-Dexterity Finger Interaction. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–13.  https://doi.org/10.1145/3290605.3300301
  * Leithinger et al. (2013) Daniel Leithinger, Sean Follmer, Alex Olwal, Samuel Luescher, Akimitsu Hogge, Jinha Lee, and Hiroshi Ishii. 2013.  Sublimate: state-changing virtual and physical rendering to augment interaction with shape displays. In _Proceedings of the SIGCHI Conference on Human Factors in Computing Systems - CHI ’13_. ACM Press, Paris, France, 1441.  https://doi.org/10.1145/2470654.2466191
  * Lepecq et al. (2008) Jean-Claude Lepecq, Lionel Bringoux, Jean-Marie Pergandi, Thelma Coyle, and Daniel Mestre. 2008\.  Afforded Actions as a Behavioral Assessment of Physical Presence.  (2008), 8.
  * Lo et al. (2018) Jo-Yu Lo, Da-Yuan Huang, Chen-Kuo Sun, Chu-En Hou, and Bing-Yu Chen. 2018.  RollingStone: Using Single Slip Taxel for Enhancing Active Finger Exploration with a Virtual Reality Controller. In _The 31st Annual ACM Symposium on User Interface Software and Technology - UIST ’18_. ACM Press, Berlin, Germany, 839–851.  https://doi.org/10.1145/3242587.3242627
  * Lopes et al. (2015) Pedro Lopes, Patrik Jonell, and Patrick Baudisch. 2015\.  Affordance++: Allowing Objects to Communicate Dynamic Use. In _Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI ’15_. ACM Press, Seoul, Republic of Korea, 2515–2524.  https://doi.org/10.1145/2702123.2702128
  * Lopes et al. (2017) Pedro Lopes, Sijing You, Lung-Pan Cheng, Sebastian Marwecki, and Patrick Baudisch. 2017.  Providing Haptics to Walls & Heavy Objects in Virtual Reality by Means of Electrical Muscle Stimulation. In _Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems - CHI ’17_. ACM Press, Denver, Colorado, USA, 1471–1482.  https://doi.org/10.1145/3025453.3025600
  * Lécuyer (2009) Anatole Lécuyer. 2009\.  Simulating Haptic Feedback Using Vision: A Survey of Research and Applications of Pseudo-Haptic Feedback.  _Presence: Teleoperators and Virtual Environments_ 18, 1 (Feb. 2009), 39–53.  https://doi.org/10.1162/pres.18.1.39
  * Magnenat-Thalmann et al. (2005) N. Magnenat-Thalmann, HyungSeok Kim, A. Egges, and S. Garchery. 2005.  Believability and Interaction in Virtual Worlds. In _11th International Multimedia Modelling Conference_. IEEE, Honolulu, HI, USA, 2–9.  https://doi.org/10.1109/MMMC.2005.24
  * Makin et al. (2019) Lawrence Makin, Gareth Barnaby, and Anne Roudaut. 2019\.  Tactile and kinesthetic feedbacks improve distance perception in virtual reality. In _Proceedings of the 31st Conference on l’Interaction Homme-Machine - IHM ’19_. ACM Press, Grenoble, France, 1–9.  https://doi.org/10.1145/3366550.3372248
  * Marquardt et al. (2009) Nicolai Marquardt, Miguel A. Nacenta, James E. Young, Sheelagh Carpendale, Saul Greenberg, and Ehud Sharlin. 2009.  The Haptic Tabletop Puck: tactile feedback for interactive tabletops. In _Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces - ITS ’09_. ACM Press, Banff, Alberta, Canada, 85.  https://doi.org/10.1145/1731903.1731922
  * Massie and Salisbury (1994) Thomas H Massie and J K Salisbury. 1994.  The PHANTOM Haptic Interface: A Device for Probing Virtual Objects.  (1994), 5.
  * McNeely (1993) W. A. McNeely. 1993\.  Robotic graphics: a new approach to force feedback for virtual reality. In _Proceedings of IEEE Virtual Reality Annual International Symposium_. 336–341.  https://doi.org/10.1109/VRAIS.1993.380761
  * Merino et al. (2020) Leonel Merino, Magdalena Schwarzl, Matthias Kraus, Michael Sedlmair, Dieter Schmalstieg, and Daniel Weiskopf. 2020.  Evaluating Mixed and Augmented Reality: A Systematic Literature Review (2009-2019).  _arXiv:2010.05988 [cs]_ (Oct. 2020).  http://arxiv.org/abs/2010.05988 arXiv: 2010.05988.
  * Moline (1997) Judi Moline. 1997\.  _Virtual reality for health care: a survey_.  Technical Report.
  * Nakagaki et al. (2016a) Ken Nakagaki, Artem Dementyev, Sean Follmer, Joseph A. Paradiso, and Hiroshi Ishii. 2016a.  ChainFORM: A Linear Integrated Modular Hardware System for Shape Changing Interfaces. In _Proceedings of the 29th Annual Symposium on User Interface Software and Technology - UIST ’16_. ACM Press, Tokyo, Japan, 87–96.  https://doi.org/10.1145/2984511.2984587
  * Nakagaki et al. (2016b) Ken Nakagaki, Luke Vink, Jared Counts, Daniel Windham, Daniel Leithinger, Sean Follmer, and Hiroshi Ishii. 2016b.  Materiable: Rendering Dynamic Material Properties in Response to Direct Physical Touch with Shape Changing Interfaces. In _Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI ’16_. ACM Press, Santa Clara, California, USA, 2764–2772.  https://doi.org/10.1145/2858036.2858104
  * Nitzsche et al. (2003) Norbert Nitzsche, Uwe D. Hanebeck, and G. Schmidt. 2003\.  Design issues of mobile haptic interfaces.  _Journal of Robotic Systems_ 20, 9 (Sept. 2003), 549–556.  https://doi.org/10.1002/rob.10105
  * Norman (2013) Donald A. Norman. 2013\.  _The design of everyday things_ (revised and expanded edition ed.).  Basic Books, New York, New York.
  * Optitrack (2019) Optitrack. 2019\.  Motion Capture Systems.  http://optitrack.com/index.html
  * Ortega and Coquillart (2005) M. Ortega and S. Coquillart. 2005.  Prop-based haptic interaction with co-location and immersion: an automotive application. In _IREE International Worksho on Haptic Audio Visual Environments and their Applications, 2005._ IEEE, Ottawa, Canada, 23–28.  https://doi.org/10.1109/HAVE.2005.1545646
  * Pair et al. (2003) J. Pair, U. Neumann, D. Piepol, and B. Swartout. 2003\.  FlatWorld: combining Hollywood set-design techniques with VR.  _IEEE Computer Graphics and Applications_ 23, 1 (Jan. 2003), 12–15.  https://doi.org/10.1109/MCG.2003.1159607
  * Pavlik et al. (2013) Ryan A. Pavlik, Judy M. Vance, and Greg R. Luecke. 2013\.  Interacting With a Large Virtual Environment by Combining a Ground-Based Haptic Device and a Mobile Robot Base. In _Volume 2B: 33rd Computers and Information in Engineering Conference_. ASME, Portland, Oregon, USA, V02BT02A029.  https://doi.org/10.1115/DETC2013-13441
  * Poyade et al. (2012) M Poyade, L Molina-Tanco, A Reyes-Lecuona, A Langley, E Frutos, and S Flores. 2012\.  Validation of a haptic virtual reality simulation in the context of industrial maintenance.  (2012), 4.
  * Praveena et al. (2020) Pragathi Praveena, Daniel Rakita, Bilge Mutlu, and Michael Gleicher. 2020.  Supporting Perception of Weight through Motion-induced Sensory Conflicts in Robot Teleoperation. In _Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction_. ACM, Cambridge United Kingdom, 509–517.  https://doi.org/10.1145/3319502.3374841
  * Provancher et al. (2005) William R. Provancher, Mark R. Cutkosky, Katherine J. Kuchenbecker, and Günter Niemeyer. 2005\.  Contact Location Display for Haptic Perception of Curvature and Object Motion.  _The International Journal of Robotics Research_ 24, 9 (Sept. 2005), 691–702.  https://doi.org/10.1177/0278364905057121
  * Pusch and Lécuyer (2011) Andreas Pusch and Anatole Lécuyer. 2011.  Pseudo-haptics: from the theoretical foundations to practical system design guidelines. In _Proceedings of the 13th international conference on multimodal interfaces - ICMI ’11_. ACM Press, Alicante, Spain, 57\.  https://doi.org/10.1145/2070481.2070494
  * Putze et al. (2020) Susanne Putze, Dmitry Alexandrovsky, Felix Putze, Sebastian Höffner, Jan David Smeddinck, and Rainer Malaka. 2020.  Breaking The Experience: Effects of Questionnaires in VR User Studies. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–15.  https://doi.org/10.1145/3313831.3376144
  * Rakkolainen et al. (2020) Ismo Rakkolainen, Euan Freeman, Antti Sand, Roope Raisamo, and Stephen Brewster. 2020.  A Survey of Mid-Air Ultrasound Haptics and Its Applications.  _IEEE Transactions on Haptics_ (2020), 1–1.  https://doi.org/10.1109/TOH.2020.3018754
  * Rangarajan et al. (2020) Karan Rangarajan, Heather Davis, and Philip H. Pucher. 2020\.  Systematic Review of Virtual Haptics in Surgical Simulation: A Valid Educational Tool?  _Journal of Surgical Education_ 77, 2 (March 2020), 337–347.  https://doi.org/10.1016/j.jsurg.2019.09.006
  * Razzaque et al. (2001) Sharif Razzaque, Zachariah Kohn, and Mary C. Whitton. 2001\.  _EUROGRAPHICS 2001 / Jonathan C. Roberts Short Presentation © The Eurographics Association 2001. Redirected Walking_.
  * Rietzler et al. (2018) Michael Rietzler, Florian Geiselhart, Jan Gugenheimer, and Enrico Rukzio. 2018.  Breaking the Tracking: Enabling Weight Perception using Perceivable Tracking Offsets. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–12.  https://doi.org/10.1145/3173574.3173702
  * Rietzler et al. (2019) Michael Rietzler, Gabriel Haas, Thomas Dreja, Florian Geiselhart, and Enrico Rukzio. 2019.  Virtual Muscle Force: Communicating Kinesthetic Forces Through Pseudo-Haptic Feedback and Muscle Input. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 913–922.  https://doi.org/10.1145/3332165.3347871
  * Rubens et al. (2015) Calvin Rubens, Sean Braley, Antonio Gomes, Daniel Goc, Xujing Zhang, Juan Pablo Carrascal, and Roel Vertegaal. 2015.  BitDrones: Towards Levitating Programmable Matter Using Interactive 3D Quadcopter Displays. In _Proceedings of the 28th Annual ACM Symposium on User Interface Software & Technology - UIST ’15 Adjunct_. ACM Press, Daegu, Kyungpook, Republic of Korea, 57–58.  https://doi.org/10.1145/2815585.2817810
  * Sagayam and Hemanth (2017) K. Martin Sagayam and D. Jude Hemanth. 2017.  Hand posture and gesture recognition techniques for virtual reality applications: a survey.  _Virtual Reality_ 21, 2 (June 2017), 91–107.  https://doi.org/10.1007/s10055-016-0301-0
  * Sagheb et al. (2019) Shahabedin Sagheb, Frank Wencheng Liu, Alireza Bahremand, Assegid Kidane, and Robert LiKamWa. 2019\.  SWISH: A Shifting-Weight Interface of Simulated Hydrodynamics for Haptic Perception of Virtual Fluid Vessels. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 751–761.  https://doi.org/10.1145/3332165.3347870
  * Samad et al. (2019) Majed Samad, Elia Gatti, Anne Hermes, Hrvoje Benko, and Cesare Parise. 2019.  Pseudo-Haptic Weight: Changing the Perceived Weight of Virtual Objects By Manipulating Control-Display Ratio. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–13.  https://doi.org/10.1145/3290605.3300550
  * Satler et al. (2011) Massimo Satler, Carlo A. Avizzano, and Emanuele Ruffaldi. 2011\.  Control of a desktop mobile haptic interface. In _2011 IEEE World Haptics Conference_. IEEE, Istanbul, 415–420.  https://doi.org/10.1109/WHC.2011.5945522
  * Sato (2002) M. Sato. 2002.  SPIDAR and virtual reality. In _Proceedings of the 5th Biannual World Automation Congress_ , Vol. 13. 17–23.  https://doi.org/10.1109/WAC.2002.1049515
  * Savino (2020) Gian-Luca Savino. 2020\.  Virtual Smartphone: High Fidelity Interaction with Proxy Objects in Virtual Reality.  _arXiv:2010.00942 [cs]_ (Oct. 2020).  http://arxiv.org/abs/2010.00942 arXiv: 2010.00942.
  * Schmidt et al. (2015) Dominik Schmidt, Rob Kovacs, Vikram Mehta, Udayan Umapathi, Sven Köhler, Lung-Pan Cheng, and Patrick Baudisch. 2015.  Level-Ups: Motorized Stilts that Simulate Stair Steps in Virtual Reality. In _Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI ’15_. ACM Press, Seoul, Republic of Korea, 2157–2160.  https://doi.org/10.1145/2702123.2702253
  * Schuemie et al. (2001) Martijn J. Schuemie, Peter van der Straaten, Merel Krijn, and Charles A.P.G. van der Mast. 2001\.  Research on Presence in Virtual Reality: A Survey.  _CyberPsychology & Behavior_ 4, 2 (April 2001), 183–201.  https://doi.org/10.1089/109493101300117884
  * Schwind et al. (2019) Valentin Schwind, Pascal Knierim, Nico Haas, and Niels Henze. 2019\.  Using Presence Questionnaires in Virtual Reality. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–12.  https://doi.org/10.1145/3290605.3300590
  * Seifi et al. (2019) Hasti Seifi, Farimah Fazlollahi, Michael Oppermann, John Andrew Sastrillo, Jessica Ip, Ashutosh Agrawal, Gunhyuk Park, Katherine J. Kuchenbecker, and Karon E. MacLean. 2019.  Haptipedia: Accelerating Haptic Device Discovery to Support Interaction & Engineering Design. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–12.  https://doi.org/10.1145/3290605.3300788
  * Shaw et al. (2019) Emily Shaw, Tessa Roper, Tommy Nilsson, Glyn Lawson, Sue V. G. Cobb, and Daniel Miller. 2019\.  The Heat is On: Exploring User Behaviour in a Multisensory Virtual Environment for Fire Evacuation.  _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_ (2019), 1–13.  https://doi.org/10.1145/3290605.3300856 arXiv: 1902.04573.
  * Shigeyama et al. (2019) Jotaro Shigeyama, Takeru Hashimoto, Shigeo Yoshida, Takuji Narumi, Tomohiro Tanikawa, and Michitaka Hirose. 2019.  Transcalibur: A Weight Shifting Virtual Reality Controller for 2D Shape Rendering based on Computational Perception Model. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–11.  https://doi.org/10.1145/3290605.3300241
  * Simeone et al. (2015) Adalberto L. Simeone, Eduardo Velloso, and Hans Gellersen. 2015\.  Substitutional Reality: Using the Physical Environment to Design Virtual Reality Experiences. In _Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI ’15_. ACM Press, Seoul, Republic of Korea, 3307–3316.  https://doi.org/10.1145/2702123.2702389
  * Sinclair et al. (2019) Mike Sinclair, Eyal Ofek, Mar Gonzalez-Franco, and Christian Holz. 2019.  CapstanCrunch: A Haptic VR Controller with User-supplied Force Feedback. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 815–829.  https://doi.org/10.1145/3332165.3347891
  * Sinclair et al. (2014) Mike Sinclair, Michel Pahud, and Hrvoje Benko. 2014\.  TouchMover 2.0 - 3D touchscreen with force feedback and haptic texture. In _2014 IEEE Haptics Symposium (HAPTICS)_. IEEE, Houston, TX, USA, 1–6.  https://doi.org/10.1109/HAPTICS.2014.6775425
  * Siu et al. (2018) Alexa F. Siu, Eric J. Gonzalez, Shenli Yuan, Jason B. Ginsberg, and Sean Follmer. 2018\.  shapeShift: 2D Spatial Manipulation and Self-Actuation of Tabletop Shape Displays for Tangible and Haptic Interaction. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–13.  https://doi.org/10.1145/3173574.3173865
  * Slater (1999) Mel Slater. 1999\.  Measuring Presence: A Response to the Witmer and Singer Presence Questionnaire.  _Presence: Teleoperators and Virtual Environments_ 8, 5 (Oct. 1999), 560–565.  https://doi.org/10.1162/105474699566477 Publisher: MIT Press.
  * Slater et al. (1994) Mel Slater, Martin Usoh, and Anthony Steed. 1994.  Depth of Presence in Virtual Environments.  _Presence: Teleoperators and Virtual Environments_ 3, 2 (Jan. 1994), 130–144.  https://doi.org/10.1162/pres.1994.3.2.130
  * Steed et al. (2020) Anthony Steed, Sebastian Friston, Vijay Pawar, and David Swapp. 2020.  Docking Haptics: Extending the Reach of Haptics by Dynamic Combinations of Grounded and Worn Devices.  _arXiv:2002.06093 [cs]_ (Feb. 2020).  http://arxiv.org/abs/2002.06093 arXiv: 2002.06093.
  * Steinicke et al. (2013) Frank Steinicke, Visell Yon, Jennifer Campos, and Anatole Lecuyer (Eds.). 2013.  _Human walking in virtual environments: perception, technology, and applications_.  Springer, New York,NY.  OCLC: 856865949.
  * Strandholt et al. (2020) Patrick L. Strandholt, Oana A. Dogaru, Niels C. Nilsson, Rolf Nordahl, and Stefania Serafin. 2020\.  Knock on Wood: Combining Redirected Touching and Physical Props for Tool-Based Interaction in Virtual Reality. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–13.  https://doi.org/10.1145/3313831.3376303
  * Strasnick et al. (2018) Evan Strasnick, Christian Holz, Eyal Ofek, Mike Sinclair, and Hrvoje Benko. 2018.  Haptic Links: Bimanual Haptics for Virtual Reality Using Variable Stiffness Actuation. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–12.  https://doi.org/10.1145/3173574.3174218
  * Strohmeier et al. (2020) Paul Strohmeier, Seref Güngör, Luis Herres, Dennis Gudea, Bruno Fruchard, and Jürgen Steimle. 2020\.  bARefoot: Generating Virtual Materials using Motion Coupled Vibration in Shoes. In _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_. ACM, Virtual Event USA, 579–593.  https://doi.org/10.1145/3379337.3415828
  * Sun et al. (2019) Yuqian Sun, Shigeo Yoshida, Takuji Narumi, and Michitaka Hirose. 2019.  PaCaPa: A Handheld VR Device for Rendering Size, Shape, and Stiffness of Virtual Objects in Tool-based Interactions. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–12.  https://doi.org/10.1145/3290605.3300682
  * Sutherland (1965) Ivan Sutherland. 1965\.  The Ultimate Display.  (1965), 2.
  * Suzuki et al. (2020) Ryo Suzuki, Hooman Hedayati, Clement Zheng, James Bohn, Daniel Szafir, Ellen Yi-Luen Do, Mark D Gross, and Daniel Leithinger. 2020\.  RoomShift: Room-scale Dynamic Haptics for VR with Furniture-moving Swarm Robots.  (2020), 11.
  * Suzuki et al. (2018) Ryo Suzuki, Junichi Yamaoka, Daniel Leithinger, Tom Yeh, Mark D. Gross, Yoshihiro Kawahara, and Yasuaki Kakehi. 2018.  Dynablock: Dynamic 3D Printing for Instant and Reconstructable Shape Formation. In _The 31st Annual ACM Symposium on User Interface Software and Technology - UIST ’18_. ACM Press, Berlin, Germany, 99–111.  https://doi.org/10.1145/3242587.3242659
  * Suzuki et al. (2019) Ryo Suzuki, Clement Zheng, Yasuaki Kakehi, Tom Yeh, Ellen Yi-Luen Do, Mark D Gross, and Daniel Leithinger. 2019.  ShapeBots: Shape-changing Swarm Robots.  (2019), 13.
  * Takizawa et al. (2017) N. Takizawa, H. Yano, H. Iwata, Y. Oshiro, and N. Ohkohchi. 2017.  Encountered-Type Haptic Interface for Representation of Shape and Rigidity of 3D Virtual Objects.  _IEEE Transactions on Haptics_ 10, 4 (Oct. 2017), 500–510.  https://doi.org/10.1109/TOH.2017.2740934
  * Talvas et al. (2014) Anthony Talvas, Maud Marchal, and Anatole Lecuyer. 2014\.  A Survey on Bimanual Haptic Interaction.  _IEEE Transactions on Haptics_ 7, 3 (July 2014), 285–300.  https://doi.org/10.1109/TOH.2014.2314456
  * Teng et al. (2018) Shan-Yuan Teng, Tzu-Sheng Kuo, Chi Wang, Chi-huan Chiang, Da-Yuan Huang, Liwei Chan, and Bing-Yu Chen. 2018.  PuPoP: Pop-up Prop on Palm for Virtual Reality. In _The 31st Annual ACM Symposium on User Interface Software and Technology - UIST ’18_. ACM Press, Berlin, Germany, 5–17.  https://doi.org/10.1145/3242587.3242628
  * Teng et al. (2019) Shan-Yuan Teng, Cheng-Lung Lin, Chi-huan Chiang, Tzu-Sheng Kuo, Liwei Chan, Da-Yuan Huang, and Bing-Yu Chen. 2019.  TilePoP: Tile-type Pop-up Prop for Virtual Reality.  (2019), 11.
  * Teyssier et al. (2020) Marc Teyssier, Gilles Bailly, Catherine Pelachaud, and Eric Lecolinet. 2020.  Conveying Emotions Through Device-Initiated Touch.  _IEEE Transactions on Affective Computing_ (2020), 1–1.  https://doi.org/10.1109/TAFFC.2020.3008693
  * Tsagarakis et al. (2005) N. G. Tsagarakis, T. Horne, and D. G. Caldwell. 2005\.  SLIP AESTHEASIS: a portable 2D slip/skin stretch display for the fingertip. In _First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics Conference_. 214–219.  https://doi.org/10.1109/WHC.2005.117
  * Tsai and Chen (2019) Hsin-Ruey Tsai and Bing-Yu Chen. 2019.  ElastImpact: 2.5D Multilevel Instant Impact Using Elasticity on Head-Mounted Displays. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology_. ACM, New Orleans LA USA, 429–437.  https://doi.org/10.1145/3332165.3347931
  * Tsai and Rekimoto (2018) Hsin-Ruey Tsai and Jun Rekimoto. 2018.  ElasticVR: Providing Multi-level Active and Passive Force Feedback in Virtual Reality Using Elasticity. In _Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–4.  https://doi.org/10.1145/3170427.3186540
  * Tsykunov et al. (2019) Evgeny Tsykunov, Roman Ibrahimov, Derek Vasquez, and Dzmitry Tsetserukou. 2019.  SlingDrone: Mixed Reality System for Pointing and Interaction Using a Single Drone. In _25th ACM Symposium on Virtual Reality Software and Technology on - VRST ’19_. ACM Press, Parramatta, NSW, Australia, 1–5.  https://doi.org/10.1145/3359996.3364271
  * Tsykunov and Tsetserukou (2019) Evgeny Tsykunov and Dzmitry Tsetserukou. 2019.  WiredSwarm: High Resolution Haptic Feedback Provided by a Swarm of Drones to the User’s Fingers for VR interaction. In _25th ACM Symposium on Virtual Reality Software and Technology on - VRST ’19_. ACM Press, Parramatta, NSW, Australia, 1–2.  https://doi.org/10.1145/3359996.3364789
  * Ullrich (2012) Sebastian Ullrich. 2012\.  Haptic Palpation for Medical Simulation in Virtual Environments.  _IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS_ 18, 4 (2012), 9.
  * Usoh et al. (1999) Martin Usoh, Kevin Arthur, Mary C. Whitton, Rui Bastos, Anthony Steed, Mel Slater, and Frederick P. Brooks. 1999.  Walking > walking-in-place > flying, in virtual environments. In _Proceedings of the 26th annual conference on Computer graphics and interactive techniques - SIGGRAPH ’99_. ACM Press, Not Known, 359–364.  https://doi.org/10.1145/311535.311589
  * Usoh et al. (2000) Martin Usoh, Ernest Catena, Sima Arman, and Mel Slater. 2000\.  Using Presence Questionnaires in Reality.  _Presence: Teleoperators and Virtual Environments_ 9, 5 (Oct. 2000), 497–503.  https://doi.org/10.1162/105474600566989
  * Varalakshmi et al. (2012) Varalakshmi, Thriveni, Venugopal, and Patnaik. 2012\.  Haptics: State of the Art Survey.  _IJCSI International Journal of Computer Science Issues_ (2012).  https://core.ac.uk/download/pdf/25725449.pdf
  * Villa Salazar et al. (2020) David Steeven Villa Salazar, Claudio Pacchierotti, Xavier De Tinguy De La Girouliere, Anderson Maciel, and Maud Marchal. 2020.  Altering the Stiffness, Friction, and Shape Perception of Tangible Objects in Virtual Reality Using Wearable Haptics.  _IEEE Transactions on Haptics_ (2020), 1–1.  https://doi.org/10.1109/TOH.2020.2967389
  * Vonach et al. (2017) Emanuel Vonach, Clemens Gatterer, and Hannes Kaufmann. 2017\.  VRRobot: Robot actuated props in an infinite virtual environment. In _2017 IEEE Virtual Reality (VR)_. IEEE, Los Angeles, CA, USA, 74–83.  https://doi.org/10.1109/VR.2017.7892233
  * Wang et al. (2020b) Chi Wang, Da-Yuan Huang, Shuo-Wen Hsu, Cheng-Lung Lin, Yeu-Luen Chiu, Chu-En Hou, and Bing-Yu Chen. 2020b.  Gaiters: Exploring Skin Stretch Feedback on the Legs for Enhancing Virtual Reality Experiences.  (2020), 14.
  * Wang et al. (2020a) Dangxiao Wang, Yuan Guo, Zhang Yuru, XY Weiliang, and WWIA Jing. 2020a.  Haptic display for virtual reality: progress and challenges | Elsevier Enhanced Reader.  https://doi.org/10.3724/SP.J.2096-5796.2019.0008 ISSN: 2096-5796.
  * Wang et al. (2020d) Dangxiao Wang, Kouhei Ohnishi, and Weiliang Xu. 2020d.  Multimodal Haptic Display for Virtual Reality: A Survey.  _IEEE Transactions on Industrial Electronics_ 67, 1 (Jan. 2020), 610–623.  https://doi.org/10.1109/TIE.2019.2920602
  * Wang et al. (2020c) Yuntao Wang, Hanchuan Li, Zhengyi Cao, Huiyi Luo, Ke Ou, John Raiti, Chun Yu, Shwetak Patel, and Yuanchun Shi. 2020c.  MoveVR: Enabling Multiform Force Feedback in Virtual Reality using Household Cleaning Robot.  (2020), 12.
  * Wei et al. (2020) Tzu-Yun Wei, Hsin-Ruey Tsai, Yu-So Liao, Chieh Tsai, Yi-Shan Chen, Chi Wang, and Bing-Yu Chen. 2020.  ElastiLinks: Force Feedback between VR Controllers with Dynamic Points of Application of Force. In _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_. ACM, Virtual Event USA, 1023–1034.  https://doi.org/10.1145/3379337.3415836
  * Wexelblat (1993) Alan Wexelblat. 1993\.  Virtual reality: applications and explorations.  http://libertar.io/lab/wp-content/uploads/2016/02/Virtual.Reality.-.Applications.And_.Explorations.pdf/page=164 Myron Krueger, Artificial reality 2 An easy entry to Virtual reality Chap 7.
  * Whitmire et al. (2018) Eric Whitmire, Hrvoje Benko, Christian Holz, Eyal Ofek, and Mike Sinclair. 2018.  Haptic Revolver: Touch, Shear, Texture, and Shape Rendering on a Reconfigurable Virtual Reality Controller. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–12.  https://doi.org/10.1145/3173574.3173660
  * Winther et al. (2020) Frederik Winther, Linoj Ravindran, Kasper Paabol Svendsen, and Tiare Feuchtner. 2020.  Design and Evaluation of a VR Training Simulation for Pump Maintenance Based on a Use Case at Grundfos. In _2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)_. IEEE, Atlanta, GA, USA, 738–746.  https://doi.org/10.1109/VR46266.2020.1580939036664
  * Witmer and Singer (1998) Bob G. Witmer and Michael J. Singer. 1998.  Measuring Presence in Virtual Environments: A Presence Questionnaire.  _Presence: Teleoperators and Virtual Environments_ 7, 3 (June 1998), 225–240.  https://doi.org/10.1162/105474698565686
  * Xia et al. (2018) Haijun Xia, Sebastian Herscher, Ken Perlin, and Daniel Wigdor. 2018.  Spacetime: Enabling Fluid Individual and Collaborative Editing in Virtual Reality. In _The 31st Annual ACM Symposium on User Interface Software and Technology - UIST ’18_. ACM Press, Berlin, Germany, 853–866.  https://doi.org/10.1145/3242587.3242597
  * Xia (2016) Pingjun Xia. 2016\.  Haptics for Product Design and Manufacturing Simulation.  _IEEE Transactions on Haptics_ 9, 3 (July 2016), 358–375.  https://doi.org/10.1109/TOH.2016.2554551
  * Yamaguchi et al. (2016) Kotaro Yamaguchi, Ginga Kato, Yoshihiro Kuroda, Kiyoshi Kiyokawa, and Haruo Takemura. 2016\.  A Non-grounded and Encountered-type Haptic Display Using a Drone. In _Proceedings of the 2016 Symposium on Spatial User Interaction - SUI ’16_. ACM Press, Tokyo, Japan, 43–46.  https://doi.org/10.1145/2983310.2985746
  * Yang et al. (2019) Jackie (Junrui) Yang, Christian Holz, Eyal Ofek, and Andrew D. Wilson. 2019.  DreamWalker: Substituting Real-World Walking Experiences with a Virtual Reality. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 1093–1107.  https://doi.org/10.1145/3332165.3347875
  * Ye et al. (2019) Yuan-Syun Ye, Hsin-Yu Chen, and Liwei Chan. 2019.  Pull-Ups: Enhancing Suspension Activities in Virtual Reality with Body-Scale Kinesthetic Force Feedback. In _Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology - UIST ’19_. ACM Press, New Orleans, LA, USA, 791–801.  https://doi.org/10.1145/3332165.3347874
  * Yixian et al. (2020) Yan Yixian, Kazuki Takashima, Anthony Tang, Takayuki Tanno, Kazuyuki Fujita, and Yoshifumi Kitamura. 2020.  ZoomWalls: Dynamic Walls that Simulate Haptic Infrastructure for Room-scale VR World. In _Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology_ _(UIST ’20)_. Association for Computing Machinery, New York, NY, USA, 223–235.  https://doi.org/10.1145/3379337.3415859
  * Yokokohji et al. (1999) Yasuyoshi Yokokohji, Ralph L. Hollis, and Takeo Kanade. 1999\.  WYSIWYF Display: A Visual/Haptic Interface to Virtual Environment.  _Presence: Teleoperators and Virtual Environments_ 8, 4 (Aug. 1999), 412–434.  https://doi.org/10.1162/105474699566314
  * Yokokohji et al. (2001) Y. Yokokohji, J. Kinoshita, and T. Yoshikawa. 2001\.  Path planning for encountered-type haptic devices that render multiple objects in 3D space. In _Proceedings IEEE Virtual Reality 2001_. 271–278.  https://doi.org/10.1109/VR.2001.913796
  * Yokokohji et al. (2005) Yasuyoshi Yokokohji, Nobuhiko Muramori, Yuji Sato, and Tsuneo Yoshikawa. 2005.  _Haptic Display for Multiple Fingertip Contacts Based on the Observation of Human Grasping Behaviors_.
  * Yoshida et al. (2020) Shigeo Yoshida, Yuqian Sun, and Hideaki Kuzuoka. 2020\.  PoCoPo: Handheld Pin-based Shape Display for Haptic Rendering in Virtual Reality. In _Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems_. ACM, Honolulu HI USA, 1–13.  https://doi.org/10.1145/3313831.3376358
  * Zenner and Kruger (2017) Andre Zenner and Antonio Kruger. 2017.  Shifty: A Weight-Shifting Dynamic Passive Haptic Proxy to Enhance Object Perception in Virtual Reality.  _IEEE Transactions on Visualization and Computer Graphics_ 23, 4 (April 2017), 1285–1294.  https://doi.org/10.1109/TVCG.2017.2656978
  * Zenner and Krüger (2019) André Zenner and Antonio Krüger. 2019.  Drag:on: A Virtual Reality Controller Providing Haptic Feedback Based on Drag and Weight Shift. In _Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19_. ACM Press, Glasgow, Scotland Uk, 1–12.  https://doi.org/10.1145/3290605.3300441
  * Zhao (2009) QinPing Zhao. 2009\.  A survey on virtual reality.  _Science in China Series F: Information Sciences_ 52, 3 (March 2009), 348–400.  https://doi.org/10.1007/s11432-009-0066-0
  * Zhao and Follmer (2018) Yiwei Zhao and Sean Follmer. 2018.  A Functional Optimization Based Approach for Continuous 3D Retargeted Touch of Arbitrary, Complex Boundaries in Haptic Virtual Reality. In _Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI ’18_. ACM Press, Montreal QC, Canada, 1–12.  https://doi.org/10.1145/3173574.3174118
  * Zhao et al. (2017) Yiwei Zhao, Lawrence H. Kim, Ye Wang, Mathieu Le Goc, and Sean Follmer. 2017.  Robotic Assembly of Haptic Proxy Objects for TangibleInteraction and Virtual Reality. In _Proceedings of the Interactive Surfaces and Spaces on ZZZ - ISS ’17_. ACM Press, Brighton, United Kingdom, 82–91.  https://doi.org/10.1145/3132272.3134143
  * Zhou and Deng (2009) Ning-Ning Zhou and Yu-Long Deng. 2009.  Virtual reality: A state-of-the-art survey.  _International Journal of Automation and Computing_ 6, 4 (Nov. 2009), 319–325.  https://doi.org/10.1007/s11633-009-0319-9
  * Ziat et al. (2014) Mounia Ziat, Taylor Rolison, Andrew Shirtz, Daniel Wilbern, and Carrie Anne Balcer. 2014.  Enhancing virtual immersion through tactile feedback. In _Proceedings of the adjunct publication of the 27th annual ACM symposium on User interface software and technology - UIST’14 Adjunct_. ACM Press, Honolulu, Hawaii, USA, 65–66.  https://doi.org/10.1145/2658779.2659116
  * Zielasko and Riecke (2020) Daniel Zielasko and Bernhard E Riecke. 2020.  Either Give Me a Reason to Stand or an Opportunity to Sit in VR.  (2020), 3.
  * Zilles and Salisbury (1995) C. B. Zilles and J. K. Salisbury. 1995.  A constraint-based god-object method for haptic display. In _In International Conference on Intelligent Robots and Systems_. 146–151.
  * Zimmermann (2008) Peter Zimmermann. 2008\.  Virtual Reality Aided Design. A survey of the use of VR in automotive industry.  (Jan. 2008).  https://doi.org/10.1007/978-1-4020-8200-9_13