An Autonomous Obstacle Avoidance Method for Dual-Arm Surgical Robot Based on the Improved Artificial Potential Field Method

Most surgical robots adopt a simple master-slave control method, and their forms are transitioning from non-autonomous to semi-autonomous states. Motion planning and obstacle avoidance are essential research directions. In this regard, an obstacle avoidance method for a dual-arm surgical robot based on an improved artificial potential field is proposed. First, improve the artificial potential field method. Considering the working posture of the dual-arm surgical robot in the limited workspace, respectively apply the gravitational potential field and the repulsive potential field to each joint to achieve precise control. Secondly, in terms of collision detection, use the convex hull algorithm to convex the model, and use the GJK algorithm to calculate the distance between the obstacle and the equivalent convex body of the manipulator. The distance threshold can be manually set to alert when a collision is imminent Besides, the motion is steady by using the adaptive step size. An improved splicing path method is proposed to make the manipulator jump out of the local minimum and improve the planning efficiency. Finally, smooth the resulting path and ensure the manipulator doesn't collide. Experiments show that this study can make the dual-arm surgical robot move relatively smoothly on avoiding obstacles, which provides a reference for the automation of surgical robots.