Abstract:

In view of the problem of collision and soft tissue injury caused by the traction of dual robotic arms in robot-assisted head and neck surgery, this study uses the traditional Informed-RRT*(Informed-Rapidly Exploring Random Tree*) path planning algorithm superimposes gravitational field to reduce the blindness of path search. In order to optimize the poor guidance and low efficiency of the traditional Informed-RRT* path planning algorithm, a regression filtering mechanism is introduced to avoid the local optimal search and dynamically adjust the step size. At the same time, the planning path is optimized and redundant node removal strategy is adopted to remove redundant nodes and improve the smoothness of the path. The dual-arm coordinated path planning method is investigated based on the dual-arm collision detection method and the improved Informed-RRT* algorithm. Simulation experiments show that compared with the original algorithm, the iteration time of the proposed algorithm is reduced by 72.76%, the number of iterations is reduced by 46.39%, the average path length is reduced by 6%, and the number of nodes is reduced by 45%, which verifies the effectiveness of the improved planning algorithm.

Key words: robot system, double manipulator, head and neck surgery, multiple degrees of freedom, workspace, collision detection, path planning, track tracking