SOURCE-LINKED INTELLIGENCE
Body-Grounded Replanning for Physically Adaptive Manipulation
Manipulation requires not only reasoning about the external environment, but also about the robot's physical condition. A strategy may remain geometrically feasible while becoming physically unsuitable due to increased joint load or limited mobility, yet internal physical state is typically used only for low-level control. We propose body-grounded high-level replanning, which uses internal physical state to adapt manipulation strategies during execution. Body-state events trigger strategy replanning, and an LLM interprets the underlying joint-level state, recent execution statistics, and execu
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-24T16:00:09.000Z
First collected: 2026-09-25T06:12:46.948Z. This is not the publication date.