A Physics-Informed Collision Learning Framework for Collaborative Robot Motion Generation
The Physics-Informed Unified Differentiable Framework (PI-UDF) creates a compact system for predicting collision distances between articulated robots during motion planning. It combines robot kinematics with learnable geometry embeddings to provide a differentiable clearance term, allowing it to be used directly within model predictive control for safe, collaborative robot movements.