GSAM: A Generalizable and Safe Robotic Framework for Articulated Object Manipulation
Researchers have developed GSAM, a new robotic framework designed to improve the manipulation of articulated objects. This system uses a vision-based perceiver and a fine-tuned VLM with chain-of-thought reasoning to refine object perception. GSAM also incorporates an interaction constraint function generator and an LLM for trajectory planning, aiming to prevent collisions and enhance generalization across various object types and interaction scenarios. AI
IMPACT This framework could improve the dexterity and safety of robots in complex manipulation tasks, potentially accelerating their deployment in service industries.