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An Integrated Position-Velocity-Force Method for Safety-Enhanced Shared Control in Robot-Assisted Surgical Cutting

Xilin Xiao, Xiaojian Li, Shi Yudong, Jin Fang, Ling Li, Pengfei He, Hangjie Mo

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Abstract

Numerous studies have emphasized the application of autonomous intelligence in human-robot shared control to enhance surgical convenience and efficiency. However, the neglect of human dominance may reduce surgical safety. This paper developed a safety-enhanced human-robot shared control method by intelligently allocating control authority, with the surgeon remaining the leader during the surgical procedure. Three controllers are designed initially, including a master hand position (MP) controller and a master hand velocity (MV) controller related to the surgeon's manipulation, and a planned trajectory tracking (PT) controller related to the robot. In precision surgical manipulation scenarios, precise tracking of the human's operation is achieved by combining MP and MV controllers, while a combination of MV and PT controllers is developed in high-efficiency surgical scenarios, which relaxes the requirement for precise tracking of hand position and enables precise robot assistance guided by the velocity of human hand. The autonomous scenarios and controllers switching are accomplished through a motion fusion mechanism, which is achieved via optimizing evaluation functions that are reliant on future states. Furthermore, a force feedback mechanism is proposed to help human understand the intent of autonomous control to improve safety. The feasibility and effectiveness of this method have been validated through simulations and experiments.

Index terms

Human-Robot Collaboration Motion Control Safety in HRI