Dynamic Path Planning for the Differential Drive Mobile Robot Based on Online Metaheuristic Optimization

Mobile robots are relevant dynamic systems in recent applications. Path planning is an essential task for these since it allows them to move from one location another safely and at affordable cost. has been studied extensively static scenarios. However, when the scenarios dynamic, research limited due complexity high cost of continuously re-planning robot’s movements ensure its safety. This paper proposes a new, simple, reliable, method plan safe optimized paths differential mobile The based on online re-optimization parameters state-of-the-art deterministic path planner Bug0. Due problem, metaheuristic optimization approach adopted. utilizes metaheuristics evolutionary computation swarm intelligence find Bug0 robot approaching obstacle. proposal tested simulation, well-known methods compared, including Differential Evolution (DE), Genetic Algorithm (GA), Particle Swarm Optimization (PSO). PSO generates with best performances. In addition, results PSO-based compared different configurations, former shown be significantly better.