Human Preferred Augmented Reality Visual Cues for Remote Robot Manipulation Assistance: from Direct to Supervisory Control
Achyuthan Unni Krishnan, Tsung-Chi Lin, Zhi Li
Abstract
When humans control or supervise remote robot manipulation, augmented reality (AR) visual cues overlaid on the remote camera video stream can effectively enhance human's remote perception of task and robot states, and comprehension of the robot autonomy's capability and intent. In this work, we conducted a user study (N=18) to investigate: (RQ1) what AR cues humans prefer when controlling the robot with various levels of autonomy, and (RQ2) whether this preference can be influenced by the way humans learn to use the interface. We provided AR visual cues of various types (e.g., motion guidance, obstacle indicator, target hint, autonomy activation and intent) to assist humans to pick and place an object around an obstacle on a counter workspace. We found that: 1) Participants prefer different types of AR cues based on the level of robot autonomy; 2) The AR cues the participants prefer to use after hands-on robot operation converged to the recommendation of experienced users, and may largely differ from their initial selection based on video instruction.
BibTeX
@inproceedings{iros2023_humanpreferredau,
title = {Human Preferred Augmented Reality Visual Cues for Remote Robot Manipulation Assistance: from Direct to Supervisory Control},
author = {Achyuthan Unni Krishnan and Tsung-Chi Lin and Zhi Li},
booktitle = {IROS 2023},
year = {2023}
}