Soft Tissue Cutting
Overview
This project develops an autonomous robotic cutting framework for heterogeneous soft tissue by combining active physical perception, pre-tensioning control, and imitation learning. Tissue stiffness is estimated through an EKF-based identification method, while an information-driven exploration strategy selects informative interaction regions. The inferred physical-semantic information is then incorporated into a Diffusion Policy for real-world robotic cutting.