| Title: | OS15-4 Motion Prediction for Human-Robot Collaborative Tasks Using LSTM |
|---|---|
| Publication: | ICAROB2025 |
| Volume: | 30 |
| Pages: | 449-454 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2025.OS15-4 |
| Author(s): | Kaihei Okada, Tokuo Tsuji, Tatsuhiro Hiramitsu, Hiroaki Seki, Toshihiro Nishimura, Yosuke Suzuki, Tetsuyou Watanabe |
| Publication Date: | February 13, 2025 |
| Keywords: | Human motion prediction, LSTM, Three-dimensional human skeleton, Caregiving robots |
| Abstract: | This study proposes an assistive robot system to reduce caregiving burdens in an aging society by supporting impaired body movements. The system focuses on bimanual tasks, such as pouring a drink from a bottle into a cup. Using 3D skeletal data excluding the impaired left hand, a deep learning model (LSTM) predicts the motion stages and 3D positions of the left hand, and the robot performs the substitute motions. The system uses data from multiple users to show its potential for improving patient independence and reducing caregiver workload. |
| PDF File: | https://alife-robotics.co.jp/members2025/icarob/data/html/data/OS/OS15/OS15-4.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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