Virtual Reality and Photogrammetry for Improved Reproducibility of Human-Robot Interaction Studies
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Date
2019-08-15
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Citation of Original Publication
M. Murnane, M. Breitmeyer, C. Matuszek and D. Engel, "Virtual Reality and Photogrammetry for Improved Reproducibility of Human-Robot Interaction Studies," 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan, 2019, pp. 1092-1093. doi: 10.1109/VR.2019.8798186. URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8798186&isnumber=8797678
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© 2019 IEEE.
© 2019 IEEE.
Subjects
Virtual Reality
VR
Photogrammetry
Human-Robot Interaction
Virtual Presence
H.5.1 [Information Interfaces and Presentation]: Multimedia Information Systems—Artificial, Augmented and Virtual Realities
I.2.9 [Artificial Intelligence]: Robotics—Operator Interfaces
I.2.9 [Artificial Intelligence]: Robotics—Sensors
VR
Photogrammetry
Human-Robot Interaction
Virtual Presence
H.5.1 [Information Interfaces and Presentation]: Multimedia Information Systems—Artificial, Augmented and Virtual Realities
I.2.9 [Artificial Intelligence]: Robotics—Operator Interfaces
I.2.9 [Artificial Intelligence]: Robotics—Sensors
Abstract
Collecting data in robotics, especially human-robot interactions,
traditionally requires a physical robot in a prepared environment,
which presents substantial scalability challenges. First, robots provide many possible points of system failure, while the availability
of human participants is limited. Second, for tasks such as language learning, it is important to create environments which provide
interesting, varied use cases. Traditionally, this requires prepared
physical spaces for each scenario being studied. Finally, the expense
associated with acquiring robots and preparing spaces places serious
limitations on the reproducible quality of experiments. We therefore propose a novel mechanism for using virtual reality to simulate
robotic sensor data in a series of prepared scenarios. This allows for
a reproducible data set which other labs can recreate using commodity VR hardware. The authors demonstrate the effectiveness of this approach with an implementation that includes a simulated physical
context, a reconstruction of a human actor, and a reconstruction of
a robot. This evaluation shows that even a simple “sandbox” environment allows us to simulate robot sensor data, as well as the
movement (e.g. view-port) and speech of humans interacting with
the robot in a prescribed scenario