Target seeking behaviour of an intelligent mobile robot using advanced particle swarm optimization

The present research work aims to develop two different motion planners for an autonomous mobile robot. The developed motion planners are inspired by particle swarm optimization and are useful for generating feasible paths by the robot within its unknown environment. Each motion planner works on its own fitness function and each fitness function are modelled based on the robot sensory information. Path analysis results showed that both motion planners are generating collision free paths and reaches its destination within its workspace. Finally, comparison has been done in between the developed PSO based motion planners.