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このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/16708
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| タイトル: | A Hybrid 2-Stage Method for Robotic Planar Pushing |
| 著者: | Gao, Ziyan
Elibol, Armagan
Chong, Nak Young |
| 発行日: | 2020-06 |
| 出版者: | Korea Robotics Society |
| 誌名: | Proceedings of the 2020 17th International Conference on Ubiquitous Robots (UR) |
| 抄録: | Robotic manipulation has been applied to a particular setup and a limited number of known objects. In order to cope with these limitations, robots need to be capable of manipulating novel objects. In this work, we proposed a computationally efficient 2-stage framework for planar pushing, allowing a robot to push novel objects to a specified pose with a minimum number of steps. We developed three modules: Coarse Action Predictor (CAP), Forward Dynamic Estimator (FDE), and Physical Property Estimator (PPE). CAP predicts a mixture of Gaussian distribution of actions. FPE learns the causality between action and successive object state. PPE based on Recurrent Neural Network predicts the physical center of mass (PCOM) from the visual center of mass (VCOM) and robot-object interaction. Our preliminary experiments show the promising results to meet the required capability of pushing novel objects. |
| Rights: | Ziyan Gao, Armagan Elibol, Nak Young Chong, A Hybrid 2-Stage Method for Robotic Planar Pushing, Proceedings of the 2020 17th International Conference on Ubiquitous Robots (UR), Kyoto, Japan, June 22-26, Late Breaking Results Paper, 2020. This material is posted here with permission of Korea Robotics Society (KROS). |
| URI: | http://hdl.handle.net/10119/16708 |
| 資料タイプ: | author |
| 出現コレクション: | b10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| C5_UR20_0191_FI.pdf | | 545Kb | Adobe PDF | 見る/開く |
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