Robot path planning in uncertain environments based on particle swarm optimization

— We propose a robot path planning method based on particle swarm optimization in an uncertain environment. We consider the case that a robot’s cognition to its environment is not complete, i.e., the information of these obstacles in the environment is uncertain. We firstly construct a global environment model based on the uncertain information of these obstacles, and then give a globally optimal path by using particle swarm optimization. Finally, we present a local optimal strategy to handle the uncertain information detected by the robot in real-time. Our preliminary simulation results show that the proposed method is feasible and efficient.

• Type: Conference
• Year: 2009
• Where: CEC
• Authors: Dunwei Gong, Li Lu, Ming Li
• Keywords: Artificial Intelligence, CEC 2009, Particle Swarm Optimization, Uncertain Environment, Uncertain Information