Obstacle avoidance algorithm for dualarm robots based on task switching With the gradual popularization of robots, safety in operation has attracted more and more attention. Due to the existence of realtime obstacles, the safe workspace of robots is gradually compressed, and the original planned path will also lead to failure. In order to ensure that the robot will not be affected in operation, an online obstacle avoidance algorithm based on the offline trajectory is proposed in this paper. The algorithm divides the operation of the manipulator into two parts, one is to attract the main motion along the offline trajectory, the other is to avoid obstacles. By choosing obstacle avoidance parameters, the robot can switch between primary and secondary movements in realtime to avoid obstacles. Two special examples are selected in the postsimulation. One is the robot avoiding the fist model of the person fitted to the sphere, and the other is the simulation experiment of the selfavoidance obstacle of the dualarm robot. Simulation experiments and data results show that the algorithm proposed in this paper has strong practicability.

Dynamic Obstacle Avoidance Planning for Manipulators of Home With the maturity of robotics and serious aging situation, home service robots have been prevailing around the world, which requires the robotic arm of home service robots to be flexible for obstacle avoidance to work in complex and changing home environment. Based on the actual requirements of home service robots, this paper proposes an obstacle avoidance planning algorithm based on improved artificial potential field method for dynamic obstacle avoidance of redundant manipulators. The velocity of the target object and obstacle were introduced into the endplanned field structure to plan a collisionfree path for the end of the arm and track the dynamic target point. Meanwhile, the deviation speed of the arm member in the obstacle repulsive field was added to ensure obstacle avoidance. Finally, the effectiveness of the algorithm was verified in the simulation environment.