IEEE Robotics & Automation Magazine - March 2022 - 43

Additionally, experimentation techniques seen in the field
of general VR may aid in administering questionnaires and
gathering participant feedback. The typical questionnaires
administered by VAM-HRI researchers can be quite jarring
for participants who experience extreme context shifts
between virtual worlds (where the study took place) and the
real world (where the feedback is gathered). This represents a
potential confounding factor for participants who no longer
visually reference what they are evaluating and may romanticize
or incorrectly remember experimental stimuli they can
no longer see.
The field of VR has similar challenges, and some studies
have started to provide in situ evaluations where questionnaires
are posed to users within the virtual environments
[12]. We are beginning to see this trend of in situ surveys in
VAM-HRI as well. In the CoBot Studio project, surveys are
administered within the experiment's virtual setting, removing
the confounding factors of 1) reality-virtuality context
shifts (having to leave the immersive virtual environment by
taking off an HMD to take a midtask survey) and 2) retrospective
surveys provided well after exposure to experimental
stimuli [14].
However, the cross-disciplinary trends and ideas from
the field of VR are not unidirectional; VAM-HRI is currently
posed to inform and improve the field of VR in return.
Enhancing immersion has always been a primary goal of the
field of VR since its inception many decades ago. With the
rise of mass-produced consumer-grade HMDs, visual
immersion has reached new heights for users around the
world. However, the challenge of providing physical immersion
through the use of haptics has largely remained an
open question: How can a user reach out and touch a
dynamic character in a virtual world? Research in VAMHRI
has proposed a potential solution for dynamic haptics,
where robots mimic the poses and movements of virtual
dynamic objects. Work by Wadgaonkar et al. [22] exemplifies
the notion of VAM-HRI supporting the field of VR with
robots acting as dynamic haptic devices and allowing users
to touch characters in virtual worlds and further enhance
immersion in VR settings.
Advancements in VAM-HRI
A strength of VAM-HRI is the ability to alter a robot's morphology
with virtual imagery. This technique can take the
form of body extensions, where virtual appendages, such as
limbs, are added to a real robot [7] or the formation of transformations
where the robot's entire morphology is altered,
such as transforming a drone into a floating eye [23]. Recent
VAM-HRI developments have further expanded upon this
idea of changing a real robot's appearance through the aforementioned
morphological alterations to include superficial
alterations as well, where virtual imagery can be used to
change a robot's cosmetic traits. Prior work has demonstrated
that robot cosmetic alterations can communicate robot internal
states (e.g., robotic system faults) [5]; however, to our
knowledge, this is the first time such superficial alterations
have been used to manipulate social interactions between
human and robot [22].
Although the interactions studied in HRI are typically
focused on those of the end user, a lesser studied category of
interaction exists: that between robots and their developers
and designers. Debugging robots often proves to be a challenging
and tedious task; robot faults and unexpected behavior
can be hard to understand or explain without parsing
through command lines
and error logs. To address
this issue, prior work in
VAM-HRI has used AR
interfaces
to enhance
debugging capabilities [4],
[16]. Work by Ikeda and
Szafir [10] in VAM-HRI
2021 has built upon these
concepts by providing in
situ AR visualizations of
robot state and intentions,
allowing users to better
compare robots' plans
with their actions when
debugging autonomous
robots. As AR hardware
becomes increasingly
intertwined with robotic
systems, debugging tools such as these will likely become
more commonplace to increase the efficiency and enjoyment
of robot design.
Finally, VAM-HRI interfaces have been a popular topic of
study within HRI for many years now, and numerous standard
methods of interacting with robots through MR or VR
have emerged (e.g., AR waypoints for navigation or AR lines
for displaying robot trajectories [23]). However, novel methods
of interacting with robots are still being designed today,
an example of which is persistent virtual shadows, aimed at
tackling the issue of knowing a robot's location when it is out
of the user's line of sight. Whereas prior solutions have tried
using 2D top-down radars for showing robot locations [23],
issues remain as interfaces such as these require that repeated
context shifts be performed by the user to look at the physical
surroundings and then to the radar. Solutions such as persistent
virtual shadows circumvent this limitation by embedding
robot location data into the user's environment, providing a
natural method of displaying a robot's location. This is a location
cue that humans have learned to interpret almost subconsciously
throughout the course of their lives. Creative
advances such as these will continue to emerge in this relatively
nascent subfield of HRI, presenting an exciting new
future for both VAM-HRI and the field of HRI as a whole.
Acknowledgments
This work was supported by the National Science Foundation
under awards IIS-1764092 and IIS-1925083. This work was
also supported by the Draper Scholar Program. Any opinions,
MARCH 2022 * IEEE ROBOTICS & AUTOMATION MAGAZINE *
43
VAM technology can
be formulated as
another robot within
a system-a robot
with nondeterministic,
nondirectly controllable
behavior but with a datarich
sensor suite.
IEEE Robotics & Automation Magazine - March 2022

Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - March 2022
