Mobile Robot SLAM Method Based On Multi-agent Particle Swarm Optimized Particle Filter

The core technology of mobile robot autonomous navigation technology is SLAM(simultaneous localization and mapping)involving the knowledge of motion control,information interaction and communication, which is widely applied in the aspect of aviation and space, agriculture, industry and commerce. Precise location and mapping in unknown environments is the most import problem of SLAM problem of mobile robots. Precise location depends on efficiency mapping, while efficiency mapping based on precise location. This paper will introduce the SLAM problem from the following four aspects:1.The task of unknown region detection and division were separately finished by the method of hilbert detection and multi-agent particle swarm optimized particle filter(MAPSOPF) algorithm.2.path planning problem is solved by the method integrating grid method, Artificial field method, fuzzy method, multi-agent particle swarm optimized particle filter. Without the collision between the robot and the obstacle, the robot reachs the end point.3.Using the competition mechanism of multi-agent system to improve the particle swarm optimization algorithm and using the improved algorithm to tackle the location problem and improve precision.4.In comparison to the single robot, robot whch using the technology of Complete network structure, blackboard mechanism, multi-agent particle swarm optimized particle filter to tackle cooperative location problem in multi-robot system can utilize the information of other robots to update the location and improve the precision.Finally, the summary of research conclusions and a discussion on the most promising paths of future research work are presented in the last chapter of this dissertation.