In order to reduce the path length of mobile robot,a navigation path planning method based on autonomous learning particle swarm algorithm is proposed.A path planning model is established aiming at reducing the path length;In order to pre-vent collision of robot,the method of obstacle expansion is given.In particle swarm optimization,a learning strategy pool com-posed of multiple particle-learning strategies is introduced,and the autonomous learning strategy of selecting learning strategies by particles is given,thus an autonomous learning particle swarm optimization algorithm with strong evolutionary ability is pro-posed.Through the algorithm performance test,the optimization ability of the autonomous learning particle swarm optimization algorithm is better than the traditional particle swarm algorithm and the improved particle swarm algorithm in reference[11];The autonomous learning particle swarm algorithm is applied to the path planning of simple scene and complex scene.The mean and standard deviation of the path planning of the algorithm are both less than those of the traditional particle swarm algorithm,which verifies the superiority of the autonomous learning particle swarm optimization algorithm in robot path planning.
Mobile RobotPath PlanningLearning Strategy PoolAutonomous Learning StrategyParticle Swa-rm Algorithm
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