Multimodal Shared Autonomy for Social Navigation Assistance of Telepresence Robots
Kenechukwu C. Mbanisi, Michael A. Gennert

TL;DR
This paper introduces a multimodal shared autonomy system for social navigation of telepresence robots, combining visual and haptic guidance to improve user experience in crowded environments.
Contribution
It presents a novel multimodal approach integrating visual and haptic cues for navigation assistance, and evaluates its effectiveness through user studies in virtual environments.
Findings
Participants preferred multimodal assistance with visual guidance.
Visual guidance improved understanding and cooperation.
No significant difference in navigation performance across modalities.
Abstract
Mobile telepresence robots (MTRs) have become increasingly popular in the expanding world of remote work, providing new avenues for people to actively participate in activities at a distance. However, humans operating MTRs often have difficulty navigating in densely populated environments due to limited situation awareness and narrow field-of-view, which reduces user acceptance and satisfaction. Shared autonomy in navigation has been studied primarily in static environments or in situations where only one pedestrian interacts with the robot. We present a multimodal shared autonomy approach, leveraging visual and haptic guidance, to provide navigation assistance for remote operators in densely-populated environments. It uses a modified form of reciprocal velocity obstacles for generating safe control inputs while taking social proxemics constraints into account. Two different visual…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVirtual Reality Applications and Impacts · Tactile and Sensory Interactions · Teleoperation and Haptic Systems
