An Improved Particle Filter SLAM Algorithm in Similar Environments

Abstract:

Because of the challenging data association in similar environments, a large number of particles are needed to improve the precision in particle filtering SLAM (simultaneous localization and mapping).An improved particle filter SLAM algorithm based on particle swarm optimization in similar environments is proposed. A multimode proposal distribution is acquired by combining the information of the odometry and the laser scanning. Particles are concentrated to the region of each posterior probability distribution maximum value by PSO. The performance of the conventional particle filter SLAM is improved. The simulation experiment results prove its effectiveness and feasibility.

• Periodical: Applied Mechanics and Materials (Volume 590)
• Pages: 677-682
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.590.677
• Online since: June 2014
• Authors: Guo Liang Zhang*, Er Liang Yao, Wen Jun Tang, Jun Xu
• Keywords: Map Construction, Particle Filter, Particle Swarm Optimization (PSO), Proposal Distribution, Simultaneous Localization

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