Abstract
Due to particle filter SLAM algorithm has particle weight degradation and particle depletion, it affects the positioning accuracy of mobile robot SLAM (simultaneous localization and mapping) algorithm. In order to effectively improve the positioning accuracy of SLAM algorithm, this paper combines the operating mechanism of particle filtering in SLAM to improve the firefly brightness formula, use the firefly position update formula, the global optimization of the dynamic balance algorithm and the local optimization ability. The simulation results show that compared with the original firefly particle filtering SLAM algorithm, the proposed method makes the particle representation more reasonable and further improves the positioning accuracy of the SLAM algorithm.
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