Human Perception-Optimized Planning for Comfortable VR-Based Telepresence

• Published in: IEEE robotics and automation letters Vol. 5; no. 4; p. 1
• Main Authors: Becerra, Israel, Suomalainen, Markku, Lozano, Eliezer, Mimnaugh, Katherine J., Murrieta-Cid, Rafael, LaValle, Steven M.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Computer simulation; Helmet mounted displays; Human Factors; Human motion; Human-Centered Robotics; Motion and Path Planning; Motion planning; Multiple objective analysis; Nausea; Pareto optimization; Perception; Planning; Resists; Robot sensing systems; Robots; Task analysis; Telepresence; Telepresence systems; Trajectory; Trajectory planning; Virtual reality; Virtual Reality and Interfaces
• ISSN: 2377-3766; 2377-3766
• DOI: 10.1109/LRA.2020.3015191

This paper introduces an emerging motion planning problem by considering a human that is immersed into the viewing perspective of a remote robot. The challenge is to make the experience both eective (such as delivering a sense of presence) and comfortable (such as avoiding adverse sickness symptoms, including nausea). We refer this challenging new area as human perception-optimized planning and propose a general multiobjective optimization framework that can be instantiated in many envisioned scenarios. We then consider a specific VR telepresence task as a case of human perception-optimized planning, in which we simulate a robot that sends 360 video to a remote user to be viewed through a head-mounted display. In this particular task, we plan trajectories that minimize VR sickness (and thereby maximize comfort). An A* type method is used to create a Pareto-optimal collection of piecewise linear trajectories while taking into account criteria that improve comfort. We conducted a study with human subjects touring a virtual museum, in which paths computed by our algorithm are compared against a reference RRT-based trajectory. Generally, users suffered less from VR sickness and preferred the paths created by the presented algorithm.