Target Searching for Multiple Robots Using Hybrid Particle Swarm and Bacterial Foraging Optimization

Abstract

Abstract Particle Swarm Optimization (PSO) and Bacterial Foraging Optimization (BFO) are both important algorithms in target searching tasks. A hybrid optimization algorithm with the advantages of PSO and BFO is proposed to overcome local minimal and slow global convergence in target searching for multiple robots. Simulation on an example of target searching is conducted to show the effectiveness of the proposed approach.