Tool Trajectory

Tool trajectory research focuses on understanding and optimizing how tools are used, encompassing both the physical path of a tool and the decision-making process behind its selection and application. Current research employs deep learning models, particularly neural networks, to optimize tool shapes and trajectories for robotic tasks, and to improve large language models' ability to select and utilize appropriate tools based on context and task requirements. This work is significant for advancing robotics, particularly in areas like surgery and manufacturing, where precise tool control and efficient tool use are crucial, and for enhancing the capabilities of AI systems to interact more effectively with the physical world.