A Taxonomy of Self-Handover
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915233264566272 |
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| author | Wake, Naoki Kanehira, Atsushi Sasabuchi, Kazuhiro Takamatsu, Jun Ikeuchi, Katsushi |
| author_facet | Wake, Naoki Kanehira, Atsushi Sasabuchi, Kazuhiro Takamatsu, Jun Ikeuchi, Katsushi |
| contents | Self-handover, transferring an object between one's own hands, is a common but understudied bimanual action. While it facilitates seamless transitions in complex tasks, the strategies underlying its execution remain largely unexplored. Here, we introduce the first systematic taxonomy of self-handover, derived from manual annotation of over 12 hours of cooking activity performed by 21 participants. Our analysis reveals that self-handover is not merely a passive transition, but a highly coordinated action involving anticipatory adjustments by both hands. As a step toward automated analysis of human manipulation, we further demonstrate the feasibility of classifying self-handover types using a state-of-the-art vision-language model. These findings offer fresh insights into bimanual coordination, underscoring the role of self-handover in enabling smooth task transitions-an ability essential for adaptive dual-arm robotics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_04939 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Taxonomy of Self-Handover Wake, Naoki Kanehira, Atsushi Sasabuchi, Kazuhiro Takamatsu, Jun Ikeuchi, Katsushi Robotics Artificial Intelligence Computer Vision and Pattern Recognition Self-handover, transferring an object between one's own hands, is a common but understudied bimanual action. While it facilitates seamless transitions in complex tasks, the strategies underlying its execution remain largely unexplored. Here, we introduce the first systematic taxonomy of self-handover, derived from manual annotation of over 12 hours of cooking activity performed by 21 participants. Our analysis reveals that self-handover is not merely a passive transition, but a highly coordinated action involving anticipatory adjustments by both hands. As a step toward automated analysis of human manipulation, we further demonstrate the feasibility of classifying self-handover types using a state-of-the-art vision-language model. These findings offer fresh insights into bimanual coordination, underscoring the role of self-handover in enabling smooth task transitions-an ability essential for adaptive dual-arm robotics. |
| title | A Taxonomy of Self-Handover |
| topic | Robotics Artificial Intelligence Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2504.04939 |