Chaotic Puma Optimizer Algorithm for controlling wheeled mobile robots

Abstract

The control of wheeled mobile robots plays a crucial role in many fields, including automation, logistics, security, and even space exploration. This paper presents a significant improvement in the control of wheeled mobile robots based on an enhanced version of the Puma optimization algorithm by integrating chaotic maps in both optimization phases, exploration and exploitation. The Chaotic Puma Optimizer Algorithm (CPOA) has been tested and proven effective on CEC’2022 benchmarks and three complex engineering problems. It has outperformed standard and improved metaheuristic algorithms in controlling nonlinear and time-varying wheeled mobile robots. The results show a notable improvement in terms of response time and stability, thus expanding the potential applications of this optimizer in various fields of engineering and robotics.