Autonomous Motion Planning for a Differential Robot using Particle Swarm Optimization

Abstract

In the field of robotics, particularly within the realm of service applications, one of the fundamental challenges lies in devising autonomous motion planning strategies for real-world environments. Addressing this issue necessitates the management of numerous variables, with the primary goal of enabling the robot to circumnavigate obstacles, attain its target destination in the most efficient manner, and adhere to the shortest possible route while prioritizing safety. Furthermore, the robot’s control mechanisms must exhibit stability, precision, and swift respon-siveness. Prompted by these requirements, this paper explores the utilization of Particle Swarm Optimization (PSO) in conjunction with a Proportional-Integral-Derivative (PID) controller to devise a motion planning strategy for a differential robot operating in a multifaceted real-world setting. The proposed control system is implemented using an ESP32 microcontroller, which serves as the foundation for the robot’s motion planning and execution capabilities. Through a series of simulations, the efficacy of the suggested approach is demonstrated, emphasizing its potential as a robust solution for addressing the complex challenge of autonomous motion planning in real-world environments.