PSO-based optimized neural network PID control approach for a four wheeled omnidirectional mobile robot

Abstract The demand for automation using mobile robots has been increased dramatically in the last decade. Nowadays, are used various applications that not attainable to humans. Omnidirectional one particular type of these robots, which center attention their maneuverability and ability track complex trajectories with ease, unlike differential counterparts. However, disadvantages is dynamical model, poses several challenges control approach. In this work, modeling a four-wheeled omnidirectional robot developed. Moreover, an intelligent Proportional Integral Derivative (PID) neural network methodology developed trajectory tracking tasks, Particle Swarm Optimization (PSO) algorithm utilized find optimized controller's weights. simulation study conducted Simulink Matlab package, results confirmed accuracy proposed method perform tasks.