Research on Collision Avoidance Control of Multi-Arm Medical Robot Based on C-Space

Abstract

A multi-arm robot for mandible reconstruction assisted surgery is developed. It has three manipulators and eighteen degrees of freedom. In order to prevent the collision of the manipulator caused by the overlap of the motion space of the manipulator during the space positioning of the whole mandible reconstruction operation, a collision avoidance path planning method for manipulator based on C-space is proposed. In order to obtain the space non-interference posture of one manipulator, and the interference posture of the other manipulators is taken as the obstacle mapping in C-space to obtain the free space after removing obstacles. At the same time, combining with the space position of the system manipulator, the C-space mapping mathematical model of feature points and line segments is studied, and the mapping mathematical model of any point and line segment in the plane is obtained. By introducing admissibility proof lemma to weigh the evaluation function, the improved heuristic A * search algorithm is used to search the best path for collision avoidance. The collision avoidance experiment is carried out through simulation and robot platform, and finally the animal experiment is carried out. These experimental results verify the feasibility and validity of the collision avoidance path planning method for the space manipulator. INDEX TERMS C-space mapping, collision avoidance control, medical robot, multi-arm robot, path planning.

Collision avoidance trajectory planning for a dual-robot system: using a modified APF method

“…The functions of the modified attractive potential field and virtual attractive potential force are shown in Eqs. ( 13) and (14).…”

“…The result showed that the proposal can successfully achieve collision avoidance of dual manipulators system while meeting the real-time requirements for multi-manipulator cooperate assembling scenarios. However, compared to the intelligent optimization algorithms used for the dual-robot system, there are more intelligent algorithms for the single robot obstacle avoidance trajectory planning, such as the C-space algorithm [14][15][16], grids algorithm [17,18], genetic algorithm [19][20][21], ant colony algorithm [22], artificial network [23,24], and the APF method [25]. The application results of these methods in the dual-robot trajectory planning remained to be explored.…”