Development of a Multi-Robot Model for Target Identification and Tracking in Hostile Environments Using Particle Swarm Optimization Technique

The need for efficient path planning in robotics gave rise to the conception of different approaches towards its achievement. One of the many approaches that have been discovered is Particle Swarm Optimization (PSO). In this paper, Particle Swarm Optimization was used to develop a model for target identification and tracking in hostile environments using a multi-robot system. The PSO algorithm adopted was tested in a simulated environment with three obstacles and twenty robots. The performance of the algorithm was evaluated based on some metrics such as robustness, trajectory smoothness and computational time. MATLAB 2018a was used for the simulation process. At the end of the simulation, a downward sloping convergence curve with relative trajectory smoothness was gotten, which shows that the robots successfully navigated the search space toward the target, thus proving the efficiency of the algorithm. This efficiency was also demonstrated by the good performance metrics results gotten at the end of the iteration process. The results show that the algorithm is rather promising and provides an effective path planning method.