MGAPSO Algorithm Based Inverse Kinematics Solution for 2F2R Macro-Micro Robotic Arm

Abstract The accuracy and precision of the inverse kinematics solution is the key to determine the performance of the robotic arm motion. Aiming at the Particle Swarm Optimization(PSO) algorithm’s low accuracy in solving inverse kinematics of 2-link flexible macro robotic arms with 2-link rigid micro robotic arms(2F2R macro-micro robotic arm), this paper proposes the Multiple Genetic Particle Swarm Optimization algorithm (MGAPSO), which employs a hybrid inertia weight updating strategy and integrates the multiple parallel swarm search mode and the genetic mutation operation to increase the diversity of the populations and the search accuracy. In order to verify the effectiveness of MGAPSO algorithm , two sets of experiments are conducted with six test functions and 2F2R macro-micro robotic arm, respectively. Simulation results show the optimal solution accuracy of improved MGAPSO is 1.19*10-14 , which is better than other algorithms of 3.45*10-7. This paper provides a new algorithm for the inverse kinematics problem.