A Shared Control Method of Multiobjective Motion Fusion for Surgical Robot

Shared control combines human intelligence with autonomous algorithms, demonstrating potential for enhancing the intricate and dynamic operational capabilities of robots. In robotic surgery, shared control can integrate autonomous functions into master–slave control, which enables surgeons to receive certain control assistance while maintaining control of the operation. Such a shared control system must handle multiple types of dynamically changing motion tasks, for instance, trajectory tracking, obstacle avoidance, spatial constraint, and safety guarantee. This article proposes an innovative shared control method based on multiobjective motion fusion (MoMF) by integrating multiple objective controllers into master–slave control mode. In addition, a state feedback mechanism with prediction and evaluation model is developed to balance the control inputs of different control objectives. Further, an objective priority partition function is designed to overcome the conflicts between control objectives. In the proposed method, objective controllers can be added or removed as needed. The theoretical stability of the proposed MoMF method is proved. As an example, a fusion controller that considers four control objectives of a surgical cutting operation is designed to demonstrate the practicability of this method. Finally, the feasibility and effectiveness of the proposed MoMF method are validated by simulations and prosthesis experiments.