Name
Title | ||
|---|---|---|
Learning to Guide Human Attention on Mobile Telepresence Robots with 360 degrees Vision |
Abstract | ||
|---|---|---|
Mobile telepresence robots (MTRs) allow people to navigate and interact with a remote environment that is in a place other than the person's true location. Thanks to the recent advances in 360 degrees vision, many MTRs are now equipped with an all-degree visual perception capability. However, people's visual field horizontally spans only about 120 degrees of the visual field captured by the robot. To bridge this observability gap toward human-MTR shared autonomy, we have developed a framework, called GHAL360, to enable the MTR to learn a goal-oriented policy from reinforcements for guiding human attention using visual indicators. Three telepresence environments were constructed using datasets that are extracted from Matterport3D and collected from a real robot respectively. Experimental results show that GHAL360 outperformed the baselines from the literature in the efficiency of a human-MTR team completing target search tasks. A demo video is available: https://youtu.be/aGbTxCGJSDM |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/IROS51168.2021.9636607 | 2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) |
DocType | ISSN | Citations |
Conference | 2153-0858 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kishan Chandan | 1 | 0 | 1.35 |
| Jack Albertson | 2 | 0 | 0.34 |
| Xiaohan Zhang | 3 | 5 | 6.83 |
| Xiaoyang Zhang | 4 | 34 | 10.25 |
| Yao Liu | 5 | 135 | 11.40 |
| Shiqi Zhang | 6 | 119 | 22.46 |