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Motion planning is a key element of robotics since it empowers a robot tonavigate autonomously. Particle Swarm Optimization is a simple, yet a verypowerful optimization technique which has been effectively used in many complexmulti-dimensional optimization problems. This paper proposes a path planningalgorithm based on particle swarm optimization for computing a shortestcollision-free path for a mobile robot in environments populated with staticconvex obstacles. The proposed algorithm finds the optimal path by performingrandom sampling on grid lines generated between the robot start and goalpositions. Functionality of the proposed algorithm is illustrated viasimulation results for different scenarios.

Mobile Robot Path Planning in Static Environments using Particle Swarm Optimization