Energy Optimal Trajectory Planning of Welding Robot Based on Improved Particle Swarm Optimization Algorithm

In order to effectively improve the accuracy and efficiency of the robot arm's trajectory, an energy-optimal mixed polynomial interpolation method based on improved Particle Swarm Optimization (PSO) is proposed. The PSO algorithm with a compression factor is applied to optimize the minimum energy consumption points with multiple peaks. The joint position sequence corresponding to the end-point of a given manipulator's path is obtained through inverse kinematics. The motion trajectory in joint space is then fitted using a hybrid interpolation algorithm that combines a 5th-degree polynomial and a 7th-degree polynomial. The PSO algorithm with a compression factor is applied to minimize energy consumption while considering joint velocity constraints, resulting in significantly improved search speed and avoidance of local maxima. The feasibility and effectiveness of this method are verified through experiments conducted on an ABB1600 robot. The experimental results demonstrate that the energy consumption optimization model can achieve up to 38.58% reduction in energy consumption.