SurgiCLAW: An Interpretable Atomic-Skill Agent for Precision Robotic Micromanipulation
From the abstract
Recent multimodal large language models (MLLMs) and vision--language--action models have provided robots with new capabilities for long-horizon task understanding and planning. In surgical robotics, however, end-to-end prediction of low-level actions remains limited by insufficient precision, opaque decisions, and scarce data.
From the abstract. Our summary is in progress.