Using Particle Swarm Optimization for Robot Path Planning in Dynamic Environments with Moving Obstacles and Target

Robot path planning in known and dynamic environments is feasible for mobile robots and its main purpose is to find a collision free path for a robot from an initial position to a goal position in an environment with obstacles. In this paper the goal position is assumed to be moving over the time. Also our environment includes moving obstacles as well as static ones. We present a new approach for path planning mobile robots using Particle Swarm Optimization in order to minimize total path planning time while avoiding the local optimums. Simulation is used to validate and illustrate the approach.