PSO-AG: A Multi-Robot Path Planning and obstacle avoidance algorithm

Abstract

Robot path planning is one of the most challenging tasks as it involves several parameters and different constraints. Robots moving in an environment face many challenges such as avoiding obstacles. Path planning aims at directing the robot to reach a target via a collision-free path. Online Path Planning allows robots to move in an environment they do not have prior knowledge about and ought to discover while moving. This paper introduces, PSO-AG, an online multi robot path planning algorithm that combines the benefits of particle swarm optimization and Agoraphilic algorithms. In PSO-AG, particle swarm optimization works as the moving path planner that decides the next point for the robots to reach the target, and Agoraphilic works as the moving controller that steers the robots towards the target while avoiding obstacles along the path. Simulation was used to evaluate the performance of PSO-AG in different scenarios; including different sizes of robots swarms and different levels of environment difficulty; ranging from obstacle-free to partially obstructed environment. Experiments showed promising results of PSO-AG's scalability and target reaching rate.