A Multi-Objective Modified PSO for Inverse Kinematics of a 5-DOF Robotic Arm

In this paper, a new modified particle swarm optimization, m-PSO, is proposed, in which the novelty consists of proposing fitness-based optimization algorithm, PSO, adapts particles’ behavior rather than PSO parameters and where particles evolve differently considering their level optimality. A multi-objective MO, approach then built based on m-PSO. proposed method, with fitness better mean local best are only updated toward global best, while others keep moving classical manner. The m-PSO its version MO-m-PSO employed to solve inverse kinematics 5-DOF robotic arm 3D-printed for educational use. kinematics, IK problem formulated as searching an appropriate solution that takes into consideration end-effector position orientation Pareto front strategy. addressed forward model systems using Denavit–Hartenberg approach. Such allows avoid solvers challenges such singularities, may simply harm existence expression. Experimental investigations included capacity proposal handle random single points workspace also circular path planning specific orientation. comparative analysis showed mono-objective CSA, SSA. variants returned accurate results, fair solutions compared MO-PSO, MO-JAYA MO-CSA. Even if method were applied robotics arms point well geometric shape, it be transposed related industrial robotized withthe condition having model.