Interactive Motion Planning for Human-Robot Collaboration Based on Human-Centric Configuration Space Ergonomic Field
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866911322055114752 |
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| author | Li, Chenzui Chen, Yiming Wu, Xi Teng, Tao Calinon, Sylvain Caldwell, Darwin Chen, Fei |
| author_facet | Li, Chenzui Chen, Yiming Wu, Xi Teng, Tao Calinon, Sylvain Caldwell, Darwin Chen, Fei |
| contents | Industrial human-robot collaboration requires motion planning that is collision-free, responsive, and ergonomically safe to reduce fatigue and musculoskeletal risk. We propose the Configuration Space Ergonomic Field (CSEF), a continuous and differentiable field over the human joint space that quantifies ergonomic quality and provides gradients for real-time ergonomics-aware planning. An efficient algorithm constructs CSEF from established metrics with joint-wise weighting and task conditioning, and we integrate it into a gradient-based planner compatible with impedance-controlled robots. In a 2-DoF benchmark, CSEF-based planning achieves higher success rates, lower ergonomic cost, and faster computation than a task-space ergonomic planner. Hardware experiments with a dual-arm robot in unimanual guidance, collaborative drilling, and bimanual cocarrying show faster ergonomic cost reduction, closer tracking to optimized joint targets, and lower muscle activation than a point-to-point baseline. CSEF-based planning method reduces average ergonomic scores by up to 10.31% for collaborative drilling tasks and 5.60% for bimanual co-carrying tasks while decreasing activation in key muscle groups, indicating practical benefits for real-world deployment. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_14111 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Interactive Motion Planning for Human-Robot Collaboration Based on Human-Centric Configuration Space Ergonomic Field Li, Chenzui Chen, Yiming Wu, Xi Teng, Tao Calinon, Sylvain Caldwell, Darwin Chen, Fei Robotics Industrial human-robot collaboration requires motion planning that is collision-free, responsive, and ergonomically safe to reduce fatigue and musculoskeletal risk. We propose the Configuration Space Ergonomic Field (CSEF), a continuous and differentiable field over the human joint space that quantifies ergonomic quality and provides gradients for real-time ergonomics-aware planning. An efficient algorithm constructs CSEF from established metrics with joint-wise weighting and task conditioning, and we integrate it into a gradient-based planner compatible with impedance-controlled robots. In a 2-DoF benchmark, CSEF-based planning achieves higher success rates, lower ergonomic cost, and faster computation than a task-space ergonomic planner. Hardware experiments with a dual-arm robot in unimanual guidance, collaborative drilling, and bimanual cocarrying show faster ergonomic cost reduction, closer tracking to optimized joint targets, and lower muscle activation than a point-to-point baseline. CSEF-based planning method reduces average ergonomic scores by up to 10.31% for collaborative drilling tasks and 5.60% for bimanual co-carrying tasks while decreasing activation in key muscle groups, indicating practical benefits for real-world deployment. |
| title | Interactive Motion Planning for Human-Robot Collaboration Based on Human-Centric Configuration Space Ergonomic Field |
| topic | Robotics |
| url | https://arxiv.org/abs/2512.14111 |