Human Perception-Optimized Planning for Comfortable VR-Based Telepresence

This letter 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 effective (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.

Becerra Israel, Suomalainen Markku, Lozano Eliezer, Mimnaugh Katherine J., Murrieta-Cid Rafael, LaValle Steven M.

Publication type:
A1 Journal article – refereed

Place of publication:

human factors, human-centered robotics, Motion and path planning, telepresence, virtual reality and interfaces


Full citation:
I. Becerra, M. Suomalainen, E. Lozano, K. J. Mimnaugh, R. Murrieta-Cid and S. M. LaValle, “Human Perception-Optimized Planning for Comfortable VR-Based Telepresence,” in IEEE Robotics and Automation Letters, vol. 5, no. 4, pp. 6489-6496, Oct. 2020, doi: 10.1109/LRA.2020.3015191


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