Aero-plane: A Handheld Force-Feedback Device that
Renders Weight Motion Illusion on a Virtual 2D Plane
Seungwoo Je1 , Myung Jin Kim1 , Woojin Lee1 , Byungjoo Lee2 , Xing-Dong Yang3 , Pedro Lopes4 ,Andrea Bianchi1
1
Industrial Design, KAIST , Graduate School of Culture Technology, KAIST2 , Computer Science,
Dartmouth College3 , Computer Science, University of Chicago4{seungwoo_je; davidkim9404; quikhearst; byungjoo.lee; andrea}@kaist.ac.kr,
xing-dong.yang@dartmouth.edu, pedrolopes@cs.uchicago.edu
ABSTRACT

Force feedback is said to be the next frontier in virtual re­ality (VR). Recently, with consumers pushing forward withuntethered VR, researchers turned away from solutions basedon bulky hardware (e.g., exoskeletons and robotic arms) andstarted exploring smaller portable or wearable devices. How­ever, when it comes to rendering inertial forces, such as whenmoving a heavy object around or when interacting with ob­
jects with unique mass properties, current ungrounded forcefeedback devices are unable to provide quick weight shift­
ing sensations that can realistically simulate weight changes
over 2D surfaces. In this paper we introduce Aero-plane, aforce-feedback handheld controller based on two miniature jetpropellers that can render shifting weights of up to 14 N within
0.3 seconds. Through two user studies we: (1) characterize
the users’ ability to perceive and correctly recognize different
motion paths on a virtual plane while using our device; and,(2) tested the level of realism and immersion of the controller
when used in two VR applications (a rolling ball on a plane,
and using kitchen tools of different shapes and sizes). Lastly,
we present a set of applications that further explore different
usage cases and alternative form-factors for our device.
Author Keywords

Weight motion illusion; force-feedback; Virtual Reality;
VRcontroller
CCS Concepts•Human-centered computing → Haptic devices; User stud­ies; Virtual reality;
INTRODUCTION

Haptic force-feedback can signiﬁcantly enhance the user ex­perience and immersion of Virtual Reality applications [31,Permission to make digital or hard copies of all or part of this work for personal orclassroom use is granted without fee provided that copies are not made or distributedfor proﬁt or commercial advantage and that copies bear this notice and the full citationon the ﬁrst page. Copyrights for components of this work owned by others than ACM
must be honored. Abstracting with credit is permitted. To copy otherwise, or republish,
to post on servers or to redistribute to lists, requires prior speciﬁc permission and/or afee. Request permissions from permissions@acm.org.
UIST ’19, October 20-23, 2019, New Orleans, LA, USA.
Copyright © 2019 Association of Computing Machinery.
ACM ISBN 978-1-4503-6816-2/19/10 ...$15.00.
http://dx.doi.org/10.1145/3332165.3347926

Figure 1. Aero-plane is a handheld device capable of emulating a shift­
ing center of mass in 2 degrees-of-freedom by driving two jet-propellers
to generate dynamic force-feedback. Here, we demonstrate our device
rendering the weight of a virtual ball as it rolls on a virtual box that theuser is interacting with.

12, 32, 19, 8] by increasing the perceived realism of the vir­tual world. Recent efforts in the industry and academia haveattempted integrating physical proxies that enrich the haptic
experience [41, 23, 33]. At the same time, to achieve highrealism, users should also be able to freely move without theconstraints imposed by grounded hardware such as roboticarms [27], strings [14], or exoskeleton devices [5]. For suchreasons, haptic researchers have been working on ungroundedkinesthetic devices that do not trade-off haptic realism formobility, using techniques based on gyro effect [36], electri­
cal muscle stimulation [18], propellers’ thrust [11], weightshifting [10, 34], transforming the shape [17], changing thecenter of mass [30, 40], and pneumatic systems [24].
Simulating objects of different weight and center of mass isthe latest frontier in this domain. To achieve these effects,
previous research employed moving physical parts that cancreate the illusion of objects with different mass properties.
Speciﬁcally, two techniques were considered. By mechani­
cally moving weights on a 2D surface, researchers were able
to demonstrate that people can perceive static objects withdifferent centers of mass, resulting in a haptic shape illusion[30]. Other researchers [34, 40], on the other hand, focusedon creating one-dimensional dynamic changes of the centerof mass, by mechanically moving a weight (e.g., on a line).
However, no previous research was able to achieve dynamicchanges of the center of the mass on a 2D surface to repre­
sent both the weight of different objects at hand and renderchanges in weight and center of mass over time. This was
mainly due to the mechanical limitations of quickly moving
a weight in the space. Therefore, until now, it has not beenpossible to create applications that, for example, recreate themotion illusion of a ball rolling on a surface.
In this paper we present Aero-Plane, a handheld haptic device
that can render in real-time both the illusion of a weight dy­
namically moving on a virtual plane (e.g., a ball rolling on
a virtual plane), and the illusion of handling different static
objects with unique centers of mass (e.g., tools width different
weight, shape and size). We achieve this by using only two
jet-propellers, each of which can create a normal force of up
to 7 N with a low latency (from 0 to 7.1 N in 0.3 seconds). By
modulating the force of each propeller, our device creates theillusion of an object with a static weight on a virtual plane,and by dynamically adjusting these forces over time, it creates
the illusion of a weight moving on the plane.
This paper presents the following contributions. We present(1) the conceptual modeling and technical design of the Aero­
plane prototype, including an in-depth analysis of the jetpropellers for determining optimal design parameters; (2) aperception study to characterize user recognition of dynamicchanges of mass on a virtual plane; (3) a user study with afully developed Virtual Reality (VR) application to test theimmersion and realism of our system with both continuous
movements (a ball rolling on a 2D plane) and different static
objects with unique centers of mass (lifting kitchen tools); (4)a set of applications that demonstrate further usage scenarios.
RELATED WORK

Our work builds upon the ﬁeld of haptics, in particular toprevious research in haptic force feedback devices designed
to render weight or inertial forces.
Rendering weight

Rendering gravity force has numerous applications in Virtual
Reality as it enables a more realistic and immersive user experi­ence. Within the existing body of research, some work focusedon developing devices that can generate real forces [14, 22,
4, 39], while the others focused on simulating the feeling of
weight (haptic illusion) [7, 29, 18, 3]. Both approaches havepros and cons. For example, a device capable of generating
real forces can normally provide the user with a more realistic
feeling than simulation. However, the trade-off is that suchdevices often need to be externally grounded. As such, manyof them are quite bulky and thus lack in mobility.
An example of this approach is the Virtual Catch Ball [14].
The system uses a number of motor-controlled strings to pullthe user’s hand downwards to simulate gravity, using a large
setup that only works in a cave environment. SPIDER [22],on the other hand, is smaller even using a similar mechanicalstructure. The device was designed for desktop applications
but still lacks mobility. Other works use robots or robotic arms

to simulate gravity [4, 39], or even use other participants or
passive objects to provide opposing forces [6].
Another line of work simulates the feeling of weight. One
approach is to stimulate the user’s skin with mechanical defor­
mation. Grabity [7], for example, is a wearable haptic device
that simulates the feeling of a gravitational force through asym­
metric skin deformation using voice coil actuators. Similarly,
Schorr and Okamura’s ﬁnger-worn device uses skin deforma­tion to simulate the lifting of virtual objects [29]. Anotherapproach is to stimulate the user’s muscles with electrical im­
pulses on opposing muscles. For example, Lopes, et al. [18]used electrical muscle stimulation (EMS) to simulate the feel­ing of gravity while users lift or push against virtual objects.
Despite these two different approaches, the resulting devices
that simulate feeling a force are all relatively small.
Our work differs from these two groups by not only trying torender the weight of an object, but also by dynamically simu­
lating changes in the object’s displacement, which corresponds
to perceiving the weight moving on a plane over time. In sim­
ple terms, we focus on creating a weight motion illusion, sothat we can render an object moving on a surface. To achievethis, we attempted to combine the advantages of the different
methods explained above, by proposing an ungrounded (hence
mobile) controller that uses mechanical actuation to generatereal (rather than simulated) forces.

Shape/Weight changing devices

In order to simulate gravity, a device has to be able to generate
forces of different magnitudes and in various locations. In
this way, objects of different kinds and with various massproperties (e.g., center of mass) can be correctly rendered.
This is particularly important for VR applications as the type ofobjects to be simulated can be enormous. Within the existing
research, most systems are capable of relocating the center ofmass linearly in a one dimensional space [38, 40, 34, 17].
For example, the gun-shaped game controller developed by
Krekhov, et al. [17] can telescope the tube of the controller
to simulate the feeling of the user holding different types ofguns. Shifty [40] is similar in that the device uses a linear
actuator to shift a static weight along the length of a handheld
cylinder. The device was developed for VR games to simulate
the changes in the length or girth of a virtual object. TorqueBAR [34] has a similar mechanical structure, but the weight isactuated in an orthogonal direction to the handle of the device.
The main limitation of these approaches is that they are limited
to changes in one dimension.
In fact, changing the location of a static weight in a 1D space islacking in the ability to realistically simulate virtual objects ofa random shape. Transcalibur [30] was developed to overcome
this challenge using two movable bars that can open and closeon the VR handheld device. Each bar has a moving weight
actuated by a linear actuator. This allows the device to create ahaptic shape illusion of holding static objects with different 2D
shapes. iTorqU [36] adds another dimension to the existing
haptic feedback for VR controller by providing directional
torques on the device.

The main difference of our work with this literature is that oursystem is capable of delivering the illusion of a continuous
shift in the center of mass in a 2D space. In other words,
we focus on creating a dynamic weight motion illusion rather
than a shape illusion [30]. This allows us to simulate objects
that move in a virtual plane and perceive an illusion of theforce mapped to such motion. Furthermore, our system isalso different in that it was designed to minimize the usageof mechanically actuated moving parts widely used in theexisting work, by using only two static propellers to create theillusion of mass changes on a plane.
Force Feedback Using Propellers

Several devices have exploited drones and propellers thrusts
to create ungrounded force feedback. BitDrones [9], for exam­
ple, is a self-levitating display, driven by small aerial vehicles(quadcopters), each representing a 3D pixel. The user manip­ulates the pixels by pushing each quadcopter, the device inturn can provide a small force feedback to the user’s hand.
Similarly, Yamaguchi et al. [37]’s mid-air “haptic screen” is apiece of paper hung on the side of a quadcopter. The device
was designed to provide mid-air haptic feedback to simulate
the presence of a ﬂying object in VR. Tactile Drones [16] aredrone-driven ﬂying objects that creates the illusion of gameobjects bumping into the user’s body. HapticDrone [1] andHoverHaptics [2] uses a quadcopter as a kinesthetic haptic
interface to simulate objects with different levels of stiffness
and weight.
Thor’s Hammer [11] is a handheld VR controller, which pro­duces 3DoF force output on the user’s hand using six pro­pellers facing outward inside a cubic shaped device. WindBlaster [13] is a wrist-worn device using drone propellers topull the user’s wrist for VR applications. LevioPole [28] is a
rod-shaped bimanual game controller, featuring a quadcopter
on each end. The device was designed to provide resistanceforces to simulate kayaking and weightlifting experiences, andits related study and applications does not focus on generat­
ing weight illusion for rendering changes in center of mass.
Although all these devices can create forces with varying in­tensities, they have limited control over the perceived locationof the stimuli. In comparison to the existing research in thisspace, our work is different in that we contribute the designand engineering of a dual-propeller system that can precisely
create a continuous shift in the center of mass in a virtual 2D
space around a VR handheld controller.
AERO-PLANE

Aero-plane creates the illusion of a weighted object moving on
a virtual plane by modulating the speed of two propellers. As
expected the higher the thrust on these propellers, the stronger
the force that the user perceives. The key idea behind ourdesign is that the user holds the device with their hand andthus the user’s wrist becomes a pivot point. Thus, the user
perceives the change in center of mass through the changes intorque applied to the wrist via the two propellers.
First, we describe the simpler case of creating a 1D force thatsimulates a shift in weight on a line. When an object of mass
M moves from location l1 to l2 , the user experiences a force

Figure 2. Our device creates the illusion of a shifting weight because (a,b)
the thrust of its two propellers generates a force that pivots the device’s
handle around the user’s wrist. Moreover, (c) by modulating the speedof these propellers, it can mimic a weight shift on two dimensional plane(as illustrated by the X,Y coordinates above).

change from F1 to F2 , which is equivalent to the initial force
F1 multiplied by the ratio of change in location F1 × (l2 /l1 ).
Using this simple physical principle, if one generates a forcechanging from F1 to F2 , the user will experience the illusion ofa mass M moving from l1 to l2 (Figure 2.a,b.). In fact, previous
research on human perception has shown that for handheld
objects, different magnitudes of torque applied to the handcauses the user to perceive objects of different lengths [15, 25,
35].
For the 2D case, our device uses two propellers to create theillusion of an object moving on a plane. The user can perceive
the weight of a mass (M) located at a position (x,y) from thehand (i.e., the center of mass of the device, indicated in Figure
2 with a red dot) through the sum of the forces created by
the two propellers. Each propeller is represented as Fle f t andFright (Figure 2.c.). In the formula below we demonstrate how
we calculate the force required by each propeller, where lx ,ly represents the location of the propellers in relation to theuser’s hand, F represents the weight of the virtual object, andx, y represent the location of the virtual object on the 2D plane.

Fle f t =Fyx
×( − ) ,2ly lx

Fright =Fyx
×( + )
2l y lx(1)

For example, if each propeller is located lx = 15cm, ly = 7.5cm
away from the center of mass of the device, and if thevirtual object weighs 1.5N(M1 ) and is currently located at
X1 = 20cm,Y1 = 100cm on the virtual plane, then each pro­peller needs to generate the force Fle f t = 3N, Fright = 7N toaccurately depict this. On the contrary, if the object weighs
1.2N(M2 ) and is located at X2 = −20cm,Y2 = 60cm, theneach propeller must generate Fle f t = 4N, Fright = 0.8N. The
formula (1) is at the core of our control loop’s implementation.
Implementation

We now provide all technical details to assist the readers in
replicating our device. Aero-plane is based on two small jetpropeller engines (model FMS 64mm). Each of the engine is
ﬁtted with 11 EDF blades that are driven by a KV3900 brushless motor (φ 28.4 × 87.7 mm, Weight: 100 g, Voltage: 12.5

V, Max Current: 40 A). We use the force of these propellers
to generate the haptic force feedback. Each propeller can gen­erate a force between 0.5-7 N. Detailed speciﬁcations of thepropeller with the duct are described in the next section.
Mechanically, Aero-plane is composed of 3D printed cus­
tom parts made of PolyLactic Acid (PLA). Each propeller ishoused in a 72 mm diameter × 110 mm height duct with wallsof 2.5 mm thickness, located 7.5 cm laterally and 15 cm longi­
tudinally from the center of mass of the device. The weightof the two propellers and connecting parts is 400 g, and 500 g
when combined with a VIVE tracker for positional tracking.
We set the center of mass of the device in the middle of thehandle by attaching cantilevering metal weights onto the otherend of the device. The total weight of the device including
tracker and counterbalancing weight is 1069 grams. As ex­pected, the weight of the device is directly proportional to the
choice of force actuator; in the Limitations section we discussalternative conﬁgurations that trade-off haptic performancewith weight.
Aero-plane controls the motors using a set of Electronic Speed
Controller (ESC) boards (model ESC, HOBBYWING FlyFun,
rated at 40A), which are controlled via Pulse-Width Modu­
lation (PWM) with an Arduino microcontroller. The PWM
signal has a minimum and maximum value of 1.25 ms to 2 ms
and a frequency of 50 Hz (20 ms cycle). The device com­municates to VR applications via serial commands, either by
USB or Bluetooth. The entire device is powered by a Lithium
polymer battery (5000 mAh, 11.1 V, 40 C, 3S1P). Finally, thesoftware used for the measurements and for the perception
studies was written in Java, while the applications used for the
immersion/realism study were developed using Unity3D.

Figure 3. Side and top views with dimensions of our device. User holds
the device at its center-of-mass, while the jet-propellers ﬂow air upwards,
which in turn creates a downward force (depicted by the red arrows).

TECHNICAL EVALUATION OF JET-PROPELLERS

We conducted a technical evaluation of our prototype to learn
about its capabilities and limitations. We were particularlyinterested in answering four technical questions: (1) what is
the minimum force it can reliably produce?; (2) conversely,
what is its maximum force?; (3) what is the latency of ourdevice, from propellers off to an actual impulse?; and, lastly,(4) characterize the relationship between the force (in N) andthe speed of the propeller’s motors (PWM output of the motor
drivers). The next sections attempt to answer these questions
and better inform the design of the system.

System Identiﬁcation of the Rotor Actuator

No rotor actuator can produce forces with inﬁnitely high speed
and perfect accuracy. Rather, the inherent dynamics of an ac­
tuator cause the target force to be transmitted to the user in a
distorted fashion. Studies of force actuation in existing VR sys­
tems have mainly reported average and standard deviations offorces generated after a step input command and after enoughtime has passed for the actuator to reach a steady state (e.g.,[11]). However, the interactions in a typical VR application
can be so fast that the system cannot wait until the actuatorreaches the steady state (e.g., a user can move against a target
in just 300-500 ms).
In order to ensure our device can actuate quickly and reliably
we attempted to characterize its dynamics. We did so by
giving a known input to the actuator and observing the forcesthat arise from it (this standard process is denoted as system
identiﬁcation in mechanical engineering). Then, by collecting
output sample points (actuator’s response) to simple input
functions (e.g., a step function) we obtained a general functionthat can predict the output of the actuator for any other possible
inputs (also know as transfer function).
Experimental Analysis and Results

To understand the dynamics of our device, we built a testing
apparatus, which is depicted in Figure 4. As shown, we ﬁxed
the actuator at the center of our measuring cage, which wascustom-made from aluminum proﬁles. Then, we triggered ourdevice by driving the propeller with increasing PWM pulse
width. As a result, the propeller creates a pulling force inthe upward direction, and pulls on the force sensor (model
VARIENSE-FSE103) that is attached to the bottom of the cage
and connected to the actuator via a steel wire.

Figure 4. Our measurement setup (left). Close-up of how the propeller
pulls on the force sensor (right).

Using this a apparatus, we measured the pull force via theforce sensor (sampled at 250 Hz) as depicted in Figure 5. As
described above, our rotor produces minimum force at a pulse
width of 1.25 ms and maximum force at 2 ms pulse width.
In this range, we increased the magnitude of the step input
signal by 28 steps at equal intervals, input it into the rotor, andrecorded the values measured from the force sensor at eachstep. This resulted in a total of 28 step responses for the rotor
system, shown in Figure 6.
Each step response contained also the noise from the force
sensor. We removed this noise by means of low pass ﬁlter

Modelling the transfer function

We approximated the transfer function of our actuator in theform of a spring-mass-damper system (a second order system),
which is the simplest model to describe such a typical actuator.
The dynamics of a second order system can be determinedfrom its step response. Basically, the damping ratio and thenatural frequency of the system should be obtained from thestep response. Furthermore, one must add its inherent latency,
which as previously described we measured it to be around
300 ms (see Figure 8).
Figure 5. Raw and ﬁltered sensor measurementswith a half power frequency at 5 Hz (Butterworth type zerophase ﬁltering). Each step response was then analyzed using
the stepinfo function provided by MATLAB. This function
calculates the rise time, settling time, maximum settling force,and minimum settling force for a given step response — inshort, it gives us a characteristic behaviour of our actuator foreach input point.
The actuator we used required an average rise time of 823.6 ms(SD=1.317 ms), i.e., from fully off to an impulse. This was
because the response of the rotor was drastically slowed whenrendering a small force of less than 1 N (below the ﬁfth
PWM step). The average rise time of the rotor was 338 ms(SD=137 ms) in case of generating a force of more than 1
N; these larger forces are the typical use case for force feed­back devices. Also for each PWM value, the minimum andmaximum of the settling force (minimum and maximum force
once the response has risen) from the sensor are shown in the
Figure 6. On average, the force generated from the actuator
ﬂuctuates in the range of 0.8837 N (SD=0.3009 N for 28 step
responses). It can be also seen that the force output from the
input voltages exhibits a strong linear relationship (R2 =0.96
for minimum and maximum settling force); this is ideal as it
simpliﬁes controlling our device in interactive cases.
Max

Steady

100

9

90

8

80

7

70

6

60

5

50

4

40

3

30

2

20

1

10

0
1.3

1.4

1.5

1.6

1.7

1.8

1.9

−ln(%OS/100)
π 2 + ln2 (%OS/100)

2.0

Pulse width (ms)Figure 6. Measured output force (N) and noise level (dB) as we drove
our device with increasingly longer pulse widths (ms).

Characterizing our actuator’s behavior

To gain deeper insight into our actuator design, we attempted
to characterize its physical behavior. This ultimately helped
provide a more ﬁne-grained control of its haptic output capa­
bilities. We started by characterizing its transfer function, i.e.,model its force output based on the input parameters.

(2)

Furthermore, we also obtained the natural frequency (ωn ) of
the system from observing the ﬂuctuation in the ﬁltered sensor
data; this is useful to better understand the haptic noise that theuser will also feel while using our system. Figure 8 shows thatthe damped natural frequency (denoted as ωd ) of the actuatorsystem is approximately 1.5962 Hz (=1/0.6265, or 10.03 inrad/s); this is relevant because it tells us that such a device
produces some inherent haptic noise, which the user mightfeel. Using the following equation we also obtained the natural
frequency of the system, which is 2.23 Hz (14 rad/s).

ωn =

ωd
1−ζ2

(3)

Now, armed with the damping ratio and natural frequency, we
can express our device’s transfer function (denoted as H(s),and expressed in the Laplace domain):H(s) =

0
1.2

ζ=Decibel10

Decibel (dB)

Output Force (N)Min

First, the ratio of the maximum overshoot of force exerted by
the actuator to the steady state force was obtained (% OS).
The mean value obtained for the 10 step response trials inwhich overshoot was clearly observed was 4.7%. From this,the damping ratio (denoted as ζ ) was found to be 0.697, which
we obtained using the following equation:

ωn2
s2 + 2ωn ζ s + ωn2(4)Then, we used the identiﬁed transfer function to simulate how
the system will behave for any given input (thus accelerating
our experimentations drastically). Figure 7 shows the the block
diagram we constructed in Simulink. Using this model wesimulated the force output of the propellers by inputting a sinefunction at various frequencies. The delay of the system was
set to 300 ms. As a result, the actuator was able to adequately
represent the motion with a frequency of about 1 Hz. We
observed in the model that, at higher frequencies, a force ofthe desired magnitude cannot be generated or an excessively
large phase difference occurs.
In summary, each of our jet-propellers are capable of exertinga linear force between 0.5 N and 7.1 N, the average rise timeof the rotors is 0.3 seconds for conditions over 1 N up to 7.1 N.
Also, we can see that our actuator cannot implement feedbackof repeated cycles above 1 Hz. Taking into consideration
the maximum force output of each propeller, the length of theFigure 7. Simulink setup

Figure 9. Setup for our user study: participants sat down, without visualcontact with the device, and felt the pulling force of the device on their
dominant hand. Then, participants used a touchscreen with their nondominant hand to indicate the perceived weight movement.
Figure 8. Simulation result of system reaction

Material and Experimental Design

virtual handle (0.6 m) and the ratio of the virtual plane (square),the relationship between the weight of the virtual object andthe dimensions of the plane are exempliﬁed in Table 1.
We ﬁnally investigated the amount of auditory noise, power
consumption and vibration generated from the jet-propeller
when providing haptic feedback. As done by Thor’s Ham­mer [11], we measured the noise using a decibel meter (TES­
1350A) at a distance of 1 meter from the jet propeller. As
the force increases, the magnitude of the noise increases, andthe maximum magnitude is 93.5 dB at 7.1 N and 83.4 dB at
4 N (Figure 6). In comparison, Thor’s Hammer [11] has amaximum noise of 80.7 dB when using 4 N. Lastly, the power
consumption for each propeller spinning at maximum speedof 43,290 RPM (7N) is 208.2W, while vibrations amounted to
43 microns (displacement).
PERCEPTION STUDY: MOVEMENTS ON PLANE

User perception of weight shifting and changes of the center ofmass have been studied for one-dimensional movements anddiscrete transformations of objects’ shape and structure [40,34]. Currently, there are no reported studies on the perfor­
mance of people recognizing continuous weight shifts on aplane and dynamic changes of mass through kinesthetic illu­
sion. Because these two topics are interrelated, in this study
we focused on understanding the user perception performance
when recognizing continuous weight movements on a planethrough haptic illusion — meaning there are no mechanicallymoving parts to mimic the weight displacement. Speciﬁcally,
we considered 16 different one-directional movements on a
virtual 2D plane with 8 locations (as in Figure 9). We hypoth­esized that users can distinguish both the relative motion as
well as the absolute location of the starting and ending points.
Weight(N) Size of Plane (cm) Min Force (N) Max Force (N)1.2
58 x 58
0.16
6.72
1.5
40 x 400.8
71.8
28 x 28
1.92
6.96
2.1
20 x 20
2.8
7
Table 1. Relationship between perceived weight and plane dimension inforce range

Based on the results of the technical evaluation, we designed a
40cm x 40cm virtual-plane (Lx = Ly = 40cm), with the center
located at coordinates (x=0, y=80 cm) from the reference point(i.e., the device’s center of mass). Eight points are locatedaround the edge. For example, point 7 is placed at the virtual
location (0 cm, 60 cm) on the plane, 4 at (-20 cm, 80 cm),and 3 at (20 cm , 100 cm). We then designed 8 symmetricalmotion paths of length (L = 40cm) as in Figure 10. Paths along
the diagonals (hypotenuse) are shortened to match the legs’
length. Because we wanted to distinguish between back andforth directions, we considered a total of 16 motions across theplane. Motions on the plane correspond to shifting a mass of
120 grams (F = 1.2N as in [40]) along these paths, at a speedof 16.6 cm/s (i.e., 0.06 second/cm), which is the maximum
resolution obtained from Figure 9. Hence, all motion paths
take 2.4 seconds, and the forces exerted by each propeller are
within the range 0.8N ≤ Fx/y ≤ 5.6N.
Figure 9 shows the apparatus used for the study. Participants
sat down and grabbed the Aero-plane controller with their dom­
inant hand, while placing their wrist on an arm-rest. A divider
screen prevented participants from establishing visual contact
with the device. To completely cancel out any sound that could
inadvertently give away cues, participants wore both earplugs
and noise-canceling headphones that emit white noise [20].
During the study, participants felt the force feedback with
their dominant hand, while they used their non-dominant handto make input selections on a touchscreen — e.g., pressing
buttons on a GUI indicating the location and direction of theperceived weight motion.
We recruited ten participants (2 female), aged 23-33 years
old (M: 26.3, SD: 2.79), who are currently students in our
institution. Participants were compensated for their time with
10 USD in local currency.
After debrieﬁng on the experiment, the participants freely
experienced movements along the 16 paths as long as theywanted, followed by the experiment testing all 16 motion paths
in random order repeated for six blocks, for a total of 96 trials.
The ﬁrst 2 blocks were considered as training and deleted
from the analysis. Each trial started with the system placing
the object on the virtual-plane in one of the 8 predeﬁned

points (e.g., the jet-propellers were set to exert a force mapped
to the target point). Then after 2000 ms, the object moved
across the path (40cm × 16.7cm/s = 2400ms), and ﬁnally wasremoved/lifted by shutting down the jet-propellers (2000 ms
to full stop). A complete trial took 6.4 seconds. Only after
the end of a trial does the graphical interface prompt for input
from the user. During the experiment, participants took amandatory two-minute break every 16 trials but they were alsoable to stretch their wrists at any time. The experiment tookapproximately one hour to complete per participant. In total,
we collected 16 motion paths × 4 blocks × 10 participants= 640 data points.
Results and ﬁndings

For the sake of the analysis, we distinguish between the 16
motion paths as described above, and the 8 relative directions(Figure 10 - right) that describe motions with the same di­rection and orientation regardless of their origin and ending
points. For example, the paths between the points pairs 1→6,
2→8 and 3→9 all correspond to the same vertical motiona→e from top to bottom displayed in green in Figure 10. The
relative directions are computed by summing the values (e.g.,
errors) of the corresponding three absolute motions. Whilepaths describe absolute motions (i.e., the user needs to dis­tinguish both the motion and the pair of origin→end points),
the relative directions only require users to discern among thedirectional motions, regardless of their absolute location on
the plane.

Figure 10. Accuracy % and standard deviations for the 16 motion paths(left), and the 8 relative directions (right). Same directions are repre­
sented by the same colors.

Figure 11. The confusion matrix of 16 motion paths. Same directions
are represented by the same colors, as in Figure 10.

Figure 10 presents that mean accuracy and standard deviationof sixteen absolute (left) and relative (right) motions. Re­
sults were analyzed using one-way ANOVA tests followed by
Bonferroni correction post-hoc analysis with α = 0.05. We
found statistical differences for accuracy across the sixteen
motions paths (F(15,144) = 4.81, p < 0.001, η p2 = 0.33), but
no statistical difference was found across relative directions(F(7,72) = 1.967, p = 0.071, η p2 = 0.16). The post-hoc compar­
isons revealed differences between the path 4→5 and the paths
1→3, 1→6, 6→1, 8→3 and 11→10 (p < 0.05). Furthermore,
2→7 was found different than 1→3, 1→6, 6→1 and 11→10(p < 0.05).
In a post-hoc interview, participants also gave us qualitative
feedback about their experience. All participants responded
that, while it was challenging to discern the exact startingand ending location of the motion, they could easily perceive
directions and distinguish them. P3, P4, P8, P10 further ex­
plained that the left-to-right horizontal motions (e.g., 1→3,
4→5, 6→8) were among the most difﬁcult, while P3, P5, P6,
P7, P10 found difﬁcult to distinguish vertical motions (e.g.,
1→6, 2→7, 3→9). It is not surprising that people could better
distinguish relative motions than absolute positions, very simi­
lar to how haptic shape illusion can be created by alliterating
mass properties of the object without using the actual shape ofthe targeted object [30].
However, in our experiment we also found that despite difﬁ­
culties in distinguishing between absolute locations, users canapproximately distinguish the distance of the object, adding tothe overall realism of the experience. For example, P2 stated
that, “it was very fun because I could feel the movement of avirtual object“, and P5 remarked that the task “felt like han­dling an actual ball because I could feel a big change in force“.
Nevertheless, some users (P4, P7, P10) reported difﬁculties indiscerning motions that were close to each other, such as, forexample, 4→5 was easily confused with either 1→3 or 6→8.
A further analysis of the data revealed that 51.5% of the er­rors involved selecting a motion path with the same direction,parallel and immediately close to the correct target, like in the
4→5 vs. 1→3 / 6→8 case.
To summarize, based on the results of our statistical analysis
and subjective interviews, we conclude that users could suc­cessfully perceive a weight illusion of an object moving on aplane. All eight relative directions are equally well recognizedwith 81.3% (e.g., no statistical difference among directions).
Furthermore, users could also roughly distinguish between
the location of the object on the plane (e.g., near vs far), pro­vided that individual locations are far enough away from eachother. Left-to-right motions were more difﬁcult to distinguish,
and we hypothesize that this might be related to the uneven
twisting capabilities of the wrist in the two directions, andthe fact that all but one participants were right-handed. We
did not anticipate this issue and did not balance the study forhand dominance — future work might be needed to investigate
whether accuracy of motion patterns detection is correlatedwith hand dominance.

USER STUDY: REALISM AND IMMERSION

We performed a second study to understand the user’s per­ception of realism and immersion when combining the haptic
motion illusion with a visual feedback such as in a virtual real­
ity application (Figure 12 - left). We developed two different
applications in Unity3D, to exploit dynamic change of massthat creates both the illusion of a moving object (like in theperception study) and the illusion of holding different objects
with different physical properties (different weight, length,
and center of mass), conceptually similar to the haptic shapeillusion [30], but achieved through active feedback rather thanpassive feedback.

Figure 12. Ball VR application: User shown holding the device and wear­
ing a HMD (left), user point-of-view within application (right).

The ﬁrst application consists of a metal ball freely rolling inany direction on a wooden board, a setup reminiscent of that in
the perception study (Figure 12). Participants were encouraged
to roll the ball across the plane in paths of different shape andlength. They could also quickly lift the plane resulting in
the ball bouncing (implemented as a rapid absence of force,
followed by the force of the ball regaining contact with theboard).

updated. Participants could also freely experience the different
kitchen tools during the tasks.
Participants experienced the two applications with and without
haptic feedback, following a within-subjects design balanced
for the visual/haptic conditions. The visual-only condition
served as a baseline indicator. We recruited 16 participants (6female), aged 23-38 (M: 26.8, SD: 3.69), eight of which withprior experience using virtual reality applications. In eachapplication, the users held the Aero-plane device in their dom­
inant hand, while wearing a VIVE head-mounted display anda pair of noise cancelling headphones playing background mu­
sic. Participants were asked to experience the two applications
in two modalities (only visual, haptic+visual) for a duration
between 5 to 7 minutes. After each condition, participants selfassessed the level of immersion and realism of the experience(as did Lopes, et al. [18] and Zenner, et al.[40]) by complet­
ing a questionnaire with 7-points scale Likert questions. The
questionnaire also included questions about the impact of thenoise from the propellers on the user experience (is the noise
audible? is it disturbing or ruining the immersion?) as well as
application-speciﬁc questions about the realism of the motion
on the longitudinal/latitudinal axes or the rendering of differ­ent objects properties (length, weight, location of object on
the plane). The experiment concluded with a post-hoc inter­view. The experiment took about 40 minutes to complete andparticipants received 10 USD for their time.
Results

The subjective ratings for immersion and realism in the four
conditions are displayed in Figure 14.

Figure 14. Participants’ perceived immersion and perceived realism inboth VR tasks (ball and kitchen) for visual-only and visual with haptics
condition. We found that our device improves both metrics. The errorbar represents a 95% of conﬁdence interval.

Figure 13. Kitchen VR application: Different haptic feedback is given
to the user corresponding to the currently held utensil’s length, weight,
and center of mass.

The second application exploits the realism of objects withdifferent weights and physical characteristics, similar to [40,30]. The user experiences holding different cooking utensils(such as frying pans, pots, and a rolling bar) with different
lengths, weights, amount of food, and locations of the food(Figure 13). Users can switch utensils by clicking a controller
button using the non-dominant hand, and the new kitchen uten­
sil is visually displayed and the haptic feedback immediately

The results were analyzed using the Friedman test followedby post-hoc pairwise analysis with Wilcoxon signed-rank
tests. There are statistically signiﬁcant differences between
visual and visual+haptic modalities in both tasks, for both im­
mersion( X 2 (2) = 32.473, p < 0.001) and realism (X 2 (2) =34.448, p < 0.001). Post-hocs analysis reveals that the vi­
sual+haptic condition was signiﬁcantly better than the visualonly condition across the two applications for both immersion(ball application: Z = −3.53, p < 0.001, kitchen application:
Z = −3.320, p = 0.001) and realism (ball: Z = −3.422, p =0.001, kitchen: Z = −3.195, p = 0.001).
The results from the questionnaire further characterize theseresults. Participants reported their perceived level of realism(in terms of haptic-visual synchronization) via a 7-point Likert
scale (M: 5.31 SD: 1.138), the realism of the ball moving

longitudinally (M: 5.38, SD: 1.408) and of the ball moving lat­
itudinally (M: 6.13, SD: 0.806). Similar questions were asked
about the kitchen applications. Participants reported the per­ceived level of visual-haptic compliance (M:6.06 SD:0.771),
and the realism of objects with different length (M: 5.38, SD:
1.408), width (M:4.0, SD 0.478), weight (M:6.69, SD: 1.825)
and of different positions of the weight on the plane (e.g., dif­ferent food locations in the pot) (M:6.18, SD:1.328). Finally,
participants responded to the perceived noise and distractionlevel. Participants stated that they heard the noise of the pro­pellers (ball; M:4.44, SD: 1.788, kitchen; M:4.13, SD:1.893),
but that it was not distracting or reducing the immersion of theoverall experience (ball; M:3.19, SD: 1.47, kitchen; M:3.06,
SD:2.143).
Participants’ qualitative feedback

At the end of the study tasks, we asked to the participants toprovide a feedback regarding their experience. All participants
pointed out that they felt immersed and enjoyed engaging with
the VR applications using Aero-plane. For instance, P9 stated“There is a large difference between with and without haptics.”,
similarly P4 stated “When there is only visual without haptics,
I feel less immersed”; and P1 said, “It was impressive to
receive different haptic feedback depending on the item in thevirtual environment.”. Several participants, such as P7, P9,
P12, added that “It was really fun!”.
When asked to provide details on what they liked about thehaptic feedback, most participants provided explanations thatinvolved precisely the change of the center of mass. For in­
stance, P13 stated; “I liked the directionality [as the ball rolls]”;
similarly, P6 stated; “It was good to be able to feel the move­
ment of the ball as it freely rolls”; P11 stated “I liked that I
could feel the weight of this [virtual] ball.”; P7 added “The ex­perience in the kitchen was exciting and [the haptic] feedback
was appropriate.”; P11 added that the “Kitchen was very real”;
and lastly, P10 stated that “[I felt the] changes in the locationof the steak, and even the amount of meat, it felt realistic!”.
When asked which application they preferred, all but one
participant preferred the kitchen application. P2 said, “At
ﬁrst, it was awkward because I do not have prior experienceof rolling the ball in such a large plate.” P1, P15; “When I
ﬁrst feel the force, I felt the ball was heavier than I expected.”P11; “The ball moved slower than I wanted.” P14; “Kitchen
application was mapped well.” P12; “In the kitchen, I expected
it to be heavy, and I can feel it. It was great!” P1; “It wasvery realistic that the position of the food in the frying panchanged and the amount changed.” P8 who preferred the ballapplication said, “In the ball application, the continuous haptic
change was really awesome!”
Lastly, participants also mentioned possible improvements andsuggestions. Seven participants added that when they feel thewind on their face, the immersion was temporarily reduced.
Participants also commented that they initially expected theweight of the device to pose problems but it matched wellwith the virtual scenes; P11 stated,“I expected the device’s
weight to be a problem, but with the visuals, I perceived thisas the racket’s weight and was well matched”, similarly P5stated, “I expected the weight of the original frying pan when

I lifted it up, the weight of the device felt natural!”. Also, four
participants indicated that it would have been great to be able
to experience the feedback of mixing the food ingredients ofthe pot ﬁlled with food.
DISCUSSION

Aero-plane is the ﬁrst example of an ungrounded handheld haptic controller that can generate the illusion of a weight moving
on a virtual plane (weight motion illusion), as well as simulate
static objects with different center of mass (haptic shape illu­sion). By directly comparing Aero-plane with prior work, we
can further highlight the strengths of our work. Aero-plane,
like Thor’s hammer and WindBlaster [11, 13], uses propellers
to generate a force-feedback on a single hand. Our systemexerts a total force of 14 N (7.1 N per propeller), while Thor’s
hammer deliver a maximum force of 4 N, and WindBlaster of
1.5 N. Furthermore, Aero-plane can render moving weights
both faster (16.7cm/s vs the 13cm/s of Shifty [40]) and on alarger area (40 × 40cm2 area vs 48cm one-dimensional lengthof TorqueBar [34]). Finally, our paper is also the ﬁrst workthat present a quantitative analysis of the user’s perception of
motion in 2D using both absolute and relative motion stimuli.
There are two main ﬁndings from our studies. First, from theperception study, it is clear that relative motions can be moreeasily distinguished than motions between absolute locations
on the virtual plane. This is not surprising and echos qual­
itative results from previous work [30]. However, it is also
possible for users to distinguish speciﬁc locations, assumingthat these locations are not too close. Second, numerical accu­racy becomes less relevant when combining the haptic withvisual stimuli. All participants reported a high level of realism
for both the moving ball and kitchen applications, highlight­
ing the fact that measurement about haptic-visual compliance(e.g., realism, immersion, disturbance, latency) better reﬂects
the real system capabilities.
Based on these results, we developed applications for Virtualand Augmented Reality involving both weight motion andstatic rendering of different center of mass. To fully explore thepotential of the idea, we also designed controller attachmentswith different form factors to expand Aero-plane’s original
handle design. These applications are discussed next.
APPLICATIONSTaking advantage of Aero-plane’s ungrounded form factor,
continuous and dynamic force feedback, and ability to sim­
ulate different weights, we developed more examples of sce­narios and applications in which our device can be effective.
The applications partly reﬂect the contributions of some re­lated works [11, 34, 30, 17] while showcasing Aero-plane’s
strengths and competitive advantages.
Shooting Range

We have explored the potential of Aero-plane for simulating
different weights and shapes of VR objects. Additionally, con­sidering that our propellers have a short response time, quick
bursts of force feedback can be applied dynamically to render
the effect of sudden shifts in mass within a simulated object in
VR. Furthermore, by actuating the two propellers separately

properties of an object in motion in VR. In the ﬁshing scenario,
depicted in Figure 16 (right), the user holding the ﬁshing polefeels directional pull of a ﬁsh on the end of the ﬁshing line aswell as the pull toward/away from the user.

CONCLUSIONS, LIMITATIONS AND FUTURE WORK

Figure 15. Gun VR application: User shown holding the device with agun handle shaped attachment and wearing a HMD (top left). Different
haptic feedback is given to the user corresponding to the length of thegun, and muzzle rise feedback is given while the trigger is pressed.

in succession, Aero-plane can generate a quick series of suc­cessive feedback, taking only half of the response time of asingle propeller. Figure 15 depicts how Aero-plane delivers
fast force-feedback at the example of a virtual shooting range
scenario. Here, Aero-plane is not only able to simulate thechanging weights of the different guns, but also can generate
quick bursts of strong feedback to create the illusion of muzzle
rise in the user’s hands of slow or rapid ﬁring speeds. For thisapplication we 3D printed a simple handle that can be attachedto the original Aero-plane and can be held using two hands,
mimicking a gun’s grip.

Figure 16. Flight control application & Fishing application: Device is
attached to a small display running an airplane game, giving the user
tilt feedback corresponding to the game (left). User shown holding thedevice with a ﬁshing rod handle shaped attachment and wearing a HMD(middle). User’s point-of-view within the ﬁshing application (right).

Flight Control

Our Aero-plane prototype is a non-grounded haptic device thatcan generate tilting feedback around its longitudinal axis bychanging the force between propellers. In Figure 16(left), we
demonstrate this feature by attaching Aero-plane to an existing
display (e.g., a tablet) that is running a simple ﬂight simulator
game. As a result, Aero-plane enhances the ﬂight simulator
game with force feedback. In this game, the tilt of the handles
is mapped to and represents the orientation of the airplane’swings. By tilting the handles, the user can control the left andright movements of the airplane to dodge incoming obstacles.
A tilting torque is generated by the propellers that serves as
haptic feedback for the user and is mapped to the roll axis of
the airplane on the screen.
Fishing

Aero-plane can effectively render continuous and dynamic
force feedback. Using this feedback actively, the device canprovide directional cues to the user simulating the movement

In this paper we introduced Aero-plane, a propeller-based
force feedback handheld controller that can render the haptic
motion illusion of an object moving on a plane. To ﬁnd the
optimal design parameter for our design, we conducted a tech­nical evaluation, followed by two users studies to characterize
how well users can perceive motions on a plane, and how
realistic and immersive are the applications that make use of
it. Speciﬁcally, in the ﬁrst user study we found that users can
successfully perceive directional movements of a 120 g object
on a virtual plane with an average accuracy of 81%. Fromthe second study, we learned that VR graphical applications
can strongly beneﬁt from compliant haptic force feedback ofdynamic changes of mass, with both realism and immersion
rated signiﬁcantly better than in the non-haptic conditions.
Finally, we presented a set of applications that demonstrate
further ways to apply Aero-plane to VR and AR.
This work also has some limitations and possible means ofimprovement. The main issue raised in the experiments’ in­terviews is related with the overall weight of the device. Cur­
rently the device weights about 1 Kg, but this ﬁgure can belargely reduced by trading-off force for weight. For example,
by simply substituting the jet-propellers with two lighter ones
(ADF50-300L PLUS, 56g) capable of generating a total forceof 5.2 N, we can reduce the overall device weight down to 476
g. Wind and noise from the propellers were both reported todecrease immersion. Wind could be avoided by using gimbals
that keep the propellers facing earth, or by better shielding
the ducts. Noise is a more serious problem and it is sharedacross other similar propeller-based devices [13, 11]. How­ever, surprisingly, the users of our applications in the second
study reported that noise minimally impacted their experi­ence. Future work will focus on better hardware design fornoise reduction [21], though it is currently outside the scopeof this paper. Additionally, although not mentioned by theparticipants, the latency may have inﬂuenced the perceptionof realism and immersion [26] and future work will need toverify this possibility. Lastly, we received several suggestions
from users pointing to a device that could render changes ofcenter of the mass in three dimensions: for example, the users
commented that it would be interesting if they could feel the
feedback of soup stirred in a pot. Future work will attempt to
add a third dimension to the system.

ACKNOWLEDGMENTS

This research was supported by the MSIT(Ministry of Sci­
ence and ICT), Korea, under the ICT Consilience Cre­
ative program(IITP-2019-2015-0-00742) supervised by the
IITP(Institute for Information & communications Technology
Planning & Evaluation). Byungjoo Lee was supported by the
Korea Creative Content Agency (R2019020010).

[1] Muhammad Abdullah, Minji Kim, Waseem Hassan,
Yoshihiro Kuroda, and Seokhee Jeon. 2018.
HapticDrone: An encountered-type kinesthetic haptic
interface with controllable force feedback: Example ofstiffness and weight rendering. In 2018 IEEE Haptics
Symposium (HAPTICS). IEEE, 334–339.

[10] Fabian Hemmert, Susann Hamann, Matthias Löwe,
Anne Wohlauf, Joseﬁne Zeipelt, and Gesche Joost. 2010.
Take me by the hand: haptic compasses in mobile
devices through shape change and weight shift. In
Proceedings of the 6th Nordic Conference on
Human-Computer Interaction: Extending Boundaries.
ACM, 671–674.

[2] Parastoo Abtahi, Benoit Landry, Jackie Yang, Marco
Pavone, Sean Follmer, and James 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. ACM.

[11] Seongkook Heo, Christina Chung, Geehyuk Lee, andDaniel 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.
ACM, 525.

[3] Tomohiro Amemiya, Hideyuki Ando, and Taro Maeda.
2005. Virtual force display: Direction guidance using
asymmetric acceleration via periodic translationalmotion. In First Joint Eurohaptics Conference andSymposium on Haptic Interfaces for Virtual Environment
and Teleoperator Systems. World Haptics Conference.
IEEE, 619–622.

[12] Hunter G Hoffman. 1998. Physically touching virtual
objects using tactile augmentation enhances the realismof virtual environments. In Proceedings. IEEE 1998
Virtual Reality Annual International Symposium (Cat.
No. 98CB36180). IEEE, 59–63.

REFERENCES[4] Yoseph Bar-Cohen. 2003. Haptic devices for virtual
reality, telepresence, and human-assistive robotics. Biol
Inspired Intell Robots 122 (2003), 73.
[5] Craig Carignan, Jonathan Tang, and Stephen Roderick.
2009. Development of an exoskeleton haptic interface
for virtual task training. In 2009 IEEE/RSJ International
Conference on Intelligent Robots and Systems. IEEE,
3697–3702.
[6] Lung-Pan Cheng, Sebastian Marwecki, and Patrick
Baudisch. 2017. Mutual Human Actuation. In
Proceedings of the 30th Annual ACM Symposium on
User Interface Software and Technology (UIST ’17).
ACM, New York, NY, USA, 797–805. DOI:
http://dx.doi.org/10.1145/3126594.3126667[7] 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, New York, NY, USA, 119–130. DOI:
http://dx.doi.org/10.1145/3126594.3126599[8] Lukas Gehrke, Sezen Akman, Pedro Lopes, Albert
Chen, Avinash Kumar Singh, Hsiang-Ting Chen,
Chin-Teng Lin, and Klaus Gramann. 2019. Detecting
Visuo-Haptic Mismatches in Virtual Reality Using thePrediction Error Negativity of Event-Related Brain
Potentials. In Proceedings of the 2019 CHI Conferenceon Human Factors in Computing Systems (CHI ’19).
ACM, New York, NY, USA, Article 427, 11 pages. DOI:
http://dx.doi.org/10.1145/3290605.3300657[9] Antonio Gomes, Calvin Rubens, Sean Braley, and RoelVertegaal. 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.
ACM, 770–780.

[13] Seungwoo Je, Hyelip Lee, Myung Jin Kim, and Andrea
Bianchi. 2018. Wind-blaster: a wearable propeller-based
prototype that provides ungrounded force-feedback. In
ACM SIGGRAPH 2018 Emerging Technologies. ACM,
23.
[14] Seungzoo Jeong, Naoki Hashimoto, and Sato Makoto.
2004. A Novel Interaction System with Force Feedback
Between Real - and Virtual Human: An Entertainment
System: "Virtual Catch Ball". In Proceedings of the2004 ACM SIGCHI International Conference on
Advances in Computer Entertainment Technology (ACE’04). ACM, New York, NY, USA, 61–66. DOI:
http://dx.doi.org/10.1145/1067343.1067350[15] Idsart Kingma, Rolf van de Langenberg, and Peter J
Beek. 2004. Which mechanical invariants are associatedwith the perception of length and heaviness of anonvisible handheld rod? Testing the inertia tensor
hypothesis. Journal of Experimental Psychology:
Human Perception and Performance 30, 2 (2004), 346.
[16] Pascal Knierim, Thomas Kosch, Valentin Schwind,Markus Funk, Francisco Kiss, Stefan Schneegass, andNiels 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.
ACM, 433–436.
[17] Andrey Krekhov, Katharina Emmerich, Philipp
Bergmann, Sebastian Cmentowski, and Jens Krüger.
2017. Self-Transforming Controllers for Virtual Reality
First Person Shooters. In Proceedings of the Annual
Symposium on Computer-Human Interaction in Play(CHI PLAY ’17). ACM, New York, NY, USA, 517–529.
DOI:http://dx.doi.org/10.1145/3116595.3116615[18] Pedro Lopes, Sijing You, Lung-Pan Cheng, Sebastian
Marwecki, and Patrick Baudisch. 2017. Providing
haptics to walls & heavy objects in virtual reality bymeans of electrical muscle stimulation. In Proceedingsof the 2017 CHI Conference on Human Factors in
Computing Systems. ACM, 1471–1482.

[19] Karon E MacLean. 2000. Designing with haptic
feedback. In Proceedings 2000 ICRA. Millennium
Conference. IEEE International Conference on Robotics
and Automation. Symposia Proceedings (Cat. No.
00CH37065), Vol. 1. IEEE, 783–788.
[20] MC2Method. 2019. White Noise 38. (2019). Retrieved
July 15, 2019 from https://mc2method.org/white-noise/
download.php?file=38-Underwater&length=60[21] F Bruce Metzger. 1995. An assessment of propeller
aircraft noise reduction technology. Technical Report.
[22] Jun Murayama, Laroussi Bougrila, YanLin Luo,
Katsuhito Akahane, Shoichi Hasegawa, Béat
Hirsbrunner, and Makoto Sato. 2004. SPIDAR G&G: a
two-handed haptic interface for bimanual VR interaction.
In Proceedings of EuroHaptics, Vol. 2004. Citeseer,
138–146.
[23] Ken Nakagaki, Artem Dementyev, Sean Follmer,
Joseph A. Paradiso, and Hiroshi Ishii. 2016.
ChainFORM: A Linear Integrated Modular Hardware
System for Shape Changing Interfaces. In Proceedingsof the 29th Annual Symposium on User Interface
Software and Technology (UIST ’16). ACM, New York,NY, USA, 87–96. DOI:
http://dx.doi.org/10.1145/2984511.2984587[24] Ryuma Niiyama, Lining Yao, and Hiroshi Ishii. 2014.
Weight and volume changing device with liquid metaltransfer. In Proceedings of the 8th International
Conference on Tangible, Embedded and Embodied
Interaction. ACM, 49–52.
[25] Christopher C Pagano, Paula Fitzpatrick, and MT
Turvey. 1993. Tensorial basis to the constancy ofperceived object extent over variations of dynamic touch.
Perception & Psychophysics 54, 1 (1993), 43–54.
[26] Markus Rank, Zhuanghua Shi, Hermann J. Müller, andSandra Hirche. 2010. Perception of delay in haptic
telepresence systems. Presence: teleoperators andvirtual environments 19, 5 (2010), 389–399.
[27] Mikel Sagardia, Bernhard Weber, Thomas Hulin, Gerd
Hirzinger, and Carsten Preusche. 2012. Evaluation ofvisual and force feedback in virtual assembly
veriﬁcations. In 2012 IEEE Virtual Reality Workshops(VRW). IEEE, 23–26.
[28] Tomoya Sasaki, Richard Sahala Hartanto, Kao-Hua Liu,
Keitarou Tsuchiya, Atsushi Hiyama, and Masahiko
Inami. 2018. Leviopole: mid-air haptic interactions
using multirotor. In ACM SIGGRAPH 2018 Emerging
Technologies. ACM, 12.
[29] Samuel B Schorr and Allison M Okamura. 2017.
Fingertip tactile devices for virtual object manipulationand exploration. In Proceedings of the 2017 CHI
Conference on Human Factors in Computing Systems.
ACM, 3115–3119.
[30] Jotaro Shigeyama, Takeru Hashimoto, Shigeo Yoshida,
Taiju Aoki, Takuji Narumi, Tomohiro Tanikawa, andMichitaka Hirose. 2018. Transcalibur: weight moving
VR controller for dynamic rendering of 2D shape using
haptic shape illusion. In ACM SIGGRAPH 2018
Emerging Technologies. ACM, 19.
[31] Mandayam A Srinivasan and Cagatay Basdogan. 1997.
Haptics in virtual environments: Taxonomy, researchstatus, and challenges. Computers & Graphics 21, 4(1997), 393–404.
[32] Frank Steinicke, Gerd Bruder, Luv Kohli, Jason Jerald,
and Klaus Hinrichs. 2008. Taxonomy andimplementation of redirection techniques for ubiquitous
passive haptic feedback. In 2008 International
Conference on Cyberworlds. IEEE, 217–223.
[33] 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, New York, NY, USA, Article 644, 12
pages. DOI:http://dx.doi.org/10.1145/3173574.3174218[34] Colin Swindells, Alex Unden, and Tao Sang. 2003.
TorqueBAR: an ungrounded haptic feedback device. In
Proceedings of the 5th international conference on
Multimodal interfaces. ACM, 52–59.
[35] Michael T Turvey and Claudia Carello. 1995. Dynamic
touch. In Perception of space and motion. Elsevier,
401–490.
[36] Kyle N Winfree, Jamie Gewirtz, Thomas Mather,
Jonathan Fiene, and Katherine J Kuchenbecker. 2009. A
high ﬁdelity ungrounded torque feedback device: The
iTorqU 2.0. In World Haptics 2009-Third Joint
EuroHaptics conference and Symposium on Haptic
Interfaces for Virtual Environment and Teleoperator
Systems. IEEE, 261–266.
[37] Kotaro Yamaguchi, Ginga Kato, Yoshihiro Kuroda,
Kiyoshi Kiyokawa, and Haruo Takemura. 2016. A
non-grounded and encountered-type haptic display usinga drone. In Proceedings of the 2016 Symposium on
Spatial User Interaction. ACM, 43–46.
[38] Shunki Yamashita, Ryota Ishida, Arihide Takahashi,
Hsueh-Han Wu, Hironori Mitake, and Shoichi
Hasegawa. 2018. Gum-gum shooting: inducing a senseof arm elongation via forearm skin-stretch and thechange in the center of gravity. In Proceedings of the
Virtual Reality International Conference-Laval Virtual.
ACM, 21.
[39] Yasuyoshi Yokokohji, Yoshihiko Sugawara, Junji
Kinoshita, and Tsuneo Yoshikawa. 2003.
Mechano-Media that Transmit Kinesthetic Knowledge
from a Human to Other Humans. In Robotics Research,
Raymond Austin Jarvis and Alexander Zelinsky (Eds.).
Springer Berlin Heidelberg, Berlin, Heidelberg,
499–512.

[40] Andre Zenner and Antonio Krüger. 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 (2017),
1285–1294.

[41] Kening Zhu, Taizhou Chen, Feng Han, and Yi-Shiun
Wu. 2019. HapTwist: Creating Interactive Haptic
Proxies in Virtual Reality Using Low-cost Twistable
Artefacts. In Proceedings of the 2019 CHI Conferenceon Human Factors in Computing Systems (CHI ’19).
ACM, New York, NY, USA, Article 693, 13 pages. DOI:
http://dx.doi.org/10.1145/3290605.3300923