| Title: | OS7-2 POMDP-based action planning for the recognition of occluded objects with Humanoid robots |
|---|---|
| Publication: | ICAROB2020 |
| Volume: | 25 |
| Pages: | 281-284 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2020.OS7-2 |
| Author(s): | Masato Tsuru, Pierre Gergondet, Tomohiro Motoda, Adrien Escande, Eiichi Yoshida, Ixchel G. Ramirez-Alpizar, Weiwei Wan, Kensuke Harada |
| Publication Date: | January 13, 2020 |
| Keywords: | humanoid robot, POMDP, planning, point cloud, occlusion, 6DoF registration |
| Abstract: | In this paper, we present a high-layer motion planner which plans humanoid robot actions to search for object models in the robot workspace. To overcome the occlusion problem, our proposed method plans to get different perspectives of the object. POMDP (Partially Observable Markov Decision Process) is used to determine the observation pose of a robot. The planner then builds a comprehensive point cloud of by merging the point clouds gathered from different positions. The point cloud is compared to a 3D model of the object to estimate the pose of the real object. |
| PDF File: | https://alife-robotics.co.jp/members2020/icarob/data/html/data/OS/OS7/OS7-2.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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