Optimizing Redundant Robot Kinematics and Motion Planning via Advanced D-H Analysis and Enhanced Artificial Potential Fields

This paper proposes a calculation method for the optimal solution of the inverse kinematics of redundant robots. Specifically, eight sets of vector solutions of redundant robots are solved by the D-H parameter method. Then, an objective function is designed to measure the accuracy of the robot’s inverse kinematics solution and the smoothness of the robot’s joint motion. By adjusting the weights of each item, the optimal solution that meets different requirements can be selected. In addition, this paper also introduces an improved artificial potential field method to solve the problem of discontinuous changes in gravitational potential in path planning and the problem of excessive joint torque caused by excessive gravitational potential. Finally, the application of the rapidly exploring random tree (RRT) algorithm in robot path planning and obstacle avoidance is introduced. The above-mentioned calculation method and path planning algorithm were verified in the joint simulation environment of MATLAB Robot Toolbox and CoppeliaSim. The proposed inverse solution method is compared with the inverse solution generated in the CoppeliaSim simulation environment, and the angle error of each joint is less than 0.01 rad.