{"ID":2856359,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.11401","arxiv_id":"2510.11401","title":"Path and Motion Optimization for Efficient Multi-Location Inspection with Humanoid Robots","abstract":"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.","short_abstract":"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...","url_abs":"https://arxiv.org/abs/2510.11401","url_pdf":"https://arxiv.org/pdf/2510.11401v1","authors":"[\"Jiayang Wu\",\"Jiongye Li\",\"Shibowen Zhang\",\"Zhicheng He\",\"Zaijin Wang\",\"Xiaokun Leng\",\"Hangxin Liu\",\"Jingwen Zhang\",\"Jiayi Wang\",\"Song-Chun Zhu\",\"Yao Su\"]","published":"2025-10-13T13:44:08Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}