TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912155850244096 |
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| author | Wu, Jimmy Chong, William Holmberg, Robert Prasad, Aaditya Gao, Yihuai Khatib, Oussama Song, Shuran Rusinkiewicz, Szymon Bohg, Jeannette |
| author_facet | Wu, Jimmy Chong, William Holmberg, Robert Prasad, Aaditya Gao, Yihuai Khatib, Oussama Song, Shuran Rusinkiewicz, Szymon Bohg, Jeannette |
| contents | Exploiting the promise of recent advances in imitation learning for mobile manipulation will require the collection of large numbers of human-guided demonstrations. This paper proposes an open-source design for an inexpensive, robust, and flexible mobile manipulator that can support arbitrary arms, enabling a wide range of real-world household mobile manipulation tasks. Crucially, our design uses powered casters to enable the mobile base to be fully holonomic, able to control all planar degrees of freedom independently and simultaneously. This feature makes the base more maneuverable and simplifies many mobile manipulation tasks, eliminating the kinematic constraints that create complex and time-consuming motions in nonholonomic bases. We equip our robot with an intuitive mobile phone teleoperation interface to enable easy data acquisition for imitation learning. In our experiments, we use this interface to collect data and show that the resulting learned policies can successfully perform a variety of common household mobile manipulation tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_10447 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning Wu, Jimmy Chong, William Holmberg, Robert Prasad, Aaditya Gao, Yihuai Khatib, Oussama Song, Shuran Rusinkiewicz, Szymon Bohg, Jeannette Robotics Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning Exploiting the promise of recent advances in imitation learning for mobile manipulation will require the collection of large numbers of human-guided demonstrations. This paper proposes an open-source design for an inexpensive, robust, and flexible mobile manipulator that can support arbitrary arms, enabling a wide range of real-world household mobile manipulation tasks. Crucially, our design uses powered casters to enable the mobile base to be fully holonomic, able to control all planar degrees of freedom independently and simultaneously. This feature makes the base more maneuverable and simplifies many mobile manipulation tasks, eliminating the kinematic constraints that create complex and time-consuming motions in nonholonomic bases. We equip our robot with an intuitive mobile phone teleoperation interface to enable easy data acquisition for imitation learning. In our experiments, we use this interface to collect data and show that the resulting learned policies can successfully perform a variety of common household mobile manipulation tasks. |
| title | TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning |
| topic | Robotics Artificial Intelligence Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2412.10447 |