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Distributed SLAM system using particle swarm optimized particle filter for mobile robot navigation

The distributed SLAM system is a value method for mobile robot navigation. But particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involve a large number of dimensions. In this paper, the distributed particle swarm optimized particle filter was developed to improve the SLAM system. The Quantum-behaved particle swarm optimized particle filter was used to replace the local filters in distributed SLAM system. The detailed process of the improved distributed SLAM system was described. And the analysis and prove for the optimized distributed SLAM system was finished. The simulation experiment was finished using the experiment data come from an experiment that taken at Victoria Park. And the experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system has a better tolerance and robustness.