MOBILE ROBOT LOCALIZATION AND COMPOSITION BASED ON IMPROVED PSO ALGORITHM
Delving into particle filtering algorithms,particle swarm optimization algorithm was prone to local optimal solutions.The Levy step size was used to improve the weight and learning factor of PSO algorithm,thereby the optimal estimation of mobile robot position was improved.Based on FastSLAM algorithm improved by Levy PSO algorithm,the matlab software platform was used to build the map and simulation environment,clarify the specific simulation process.The average relative error of the improved FastSLAM algorithm was reduced by 13.5％,proving the effectiveness of the improved FastSLAM algorithm.The mapping experiments were conducted in complex indoor environments by ROS platform,and it had good performance index in terms of mapping performance,accuracy,and real-time performance.The relationship between the number of landmarks and system performance,as well as the relationship between robot motion path and error elimination effect,was explored through simulation experiments.
万方数据
维普
