Path and Motion Optimization for Efficient Multi-Location Inspection with Humanoid Robots
Fuente:
arXiv
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| Autores principales: | , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866917008591814656 |
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| author | Wu, Jiayang Li, Jiongye Zhang, Shibowen He, Zhicheng Wang, Zaijin Leng, Xiaokun Liu, Hangxin Zhang, Jingwen Wang, Jiayi Zhu, Song-Chun Su, Yao |
| author_facet | Wu, Jiayang Li, Jiongye Zhang, Shibowen He, Zhicheng Wang, Zaijin Leng, Xiaokun Liu, Hangxin Zhang, Jingwen Wang, Jiayi Zhu, Song-Chun Su, Yao |
| contents | This paper proposes a novel framework for humanoid robots to execute inspection tasks with high efficiency and millimeter-level precision. The approach combines hierarchical planning, time-optimal standing position generation, and integrated \ac{mpc} to achieve high speed and precision. A hierarchical planning strategy, leveraging \ac{ik} and \ac{mip}, reduces computational complexity by decoupling the high-dimensional planning problem. A novel MIP formulation optimizes standing position selection and trajectory length, minimizing task completion time. Furthermore, an MPC system with simplified kinematics and single-step position correction ensures millimeter-level end-effector tracking accuracy. Validated through simulations and experiments on the Kuavo 4Pro humanoid platform, the framework demonstrates low time cost and a high success rate in multi-location tasks, enabling efficient and precise execution of complex industrial operations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_11401 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Path and Motion Optimization for Efficient Multi-Location Inspection with Humanoid Robots Wu, Jiayang Li, Jiongye Zhang, Shibowen He, Zhicheng Wang, Zaijin Leng, Xiaokun Liu, Hangxin Zhang, Jingwen Wang, Jiayi Zhu, Song-Chun Su, Yao Robotics This paper proposes a novel framework for humanoid robots to execute inspection tasks with high efficiency and millimeter-level precision. The approach combines hierarchical planning, time-optimal standing position generation, and integrated \ac{mpc} to achieve high speed and precision. A hierarchical planning strategy, leveraging \ac{ik} and \ac{mip}, reduces computational complexity by decoupling the high-dimensional planning problem. A novel MIP formulation optimizes standing position selection and trajectory length, minimizing task completion time. Furthermore, an MPC system with simplified kinematics and single-step position correction ensures millimeter-level end-effector tracking accuracy. Validated through simulations and experiments on the Kuavo 4Pro humanoid platform, the framework demonstrates low time cost and a high success rate in multi-location tasks, enabling efficient and precise execution of complex industrial operations. |
| title | Path and Motion Optimization for Efficient Multi-Location Inspection with Humanoid Robots |
| topic | Robotics |
| url | https://arxiv.org/abs/2510.11401 |