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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2411.07534 |
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| _version_ | 1866909393684004864 |
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| author | Jorgensen, Steven Jens Bhadeshiya, Ravi |
| author_facet | Jorgensen, Steven Jens Bhadeshiya, Ravi |
| contents | We present an approach for retartgeting off-the-shelf Virtual Reality (VR) trackers to effectively teleoperate an upper-body humanoid while ensuring self-collision-free motions. Key to the effectiveness was the proper assignment of trackers to joint sets via modified task Jacobians and relaxed barrier functions for self-collision avoidance. The approach was validated on Apptronik's Astro hardware by demonstrating manipulation capabilities on a table-top environment with pick-and-place box packing and a two-handed box pick up and handover task. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_07534 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Effective Virtual Reality Teleoperation of an Upper-body Humanoid with Modified Task Jacobians and Relaxed Barrier Functions for Self-Collision Avoidance Jorgensen, Steven Jens Bhadeshiya, Ravi Robotics Machine Learning We present an approach for retartgeting off-the-shelf Virtual Reality (VR) trackers to effectively teleoperate an upper-body humanoid while ensuring self-collision-free motions. Key to the effectiveness was the proper assignment of trackers to joint sets via modified task Jacobians and relaxed barrier functions for self-collision avoidance. The approach was validated on Apptronik's Astro hardware by demonstrating manipulation capabilities on a table-top environment with pick-and-place box packing and a two-handed box pick up and handover task. |
| title | Effective Virtual Reality Teleoperation of an Upper-body Humanoid with Modified Task Jacobians and Relaxed Barrier Functions for Self-Collision Avoidance |
| topic | Robotics Machine Learning |
| url | https://arxiv.org/abs/2411.07534 |