Inertia weight analysis in particle swarm optimization for mobile robot path planning
In this study, particle swarm optimization (PSO) was implemented for a mobile robot to generate feasible paths and to investigate the effect of the inertia weight parameter at the rate of convergence. Modification of the obstacles to more complex structures creates a more complex environment for mobile robot navigation. From the simulation, different inertia weight values were tested for two obstacle configurations. The trajectory of the robotic system from the initial to the final point was smoothen using splines. It was found out that for different values of inertia weight, it abruptly or gradually decreases towards minimum distances. The key results for ω = 1.6 exhibited symmetric trajectories with a minimum distance of 474.97 cm and produced dense paths with length 525.26 cm for the first and second configurations, respectively. This method can be incorporated into existing robotic systems for more accurate, adaptive, and efficient mobile navigation.