An Optimized Coverage Robot SLAM Algorithm Based on Improved Particle Filter for WSN Nodes

An Optimized Coverage Robot SLAM Algorithm Based on Improved Particle Filter for WSN Nodes

Wei Zhang (Beihua University, Jilin City, China), Yanli Du (Beihua University, Jilin City, China) and Qinghua Bai (Beihua University, Jilin City, China)
Copyright: © 2020 |Pages: 13
DOI: 10.4018/IJGHPC.2020100106
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In order to realize the positioning and creation of the environment of mobile robots, this article proposes an optimized coverage robot SLAM algorithm based on an improved particle filter for WSN nodes. The algorithm overcomes the disadvantages of the standard particle filter SLAM algorithm in the simultaneous positioning of robot poses and creation of environmental maps. By constructing the sensor node to cover the high coverage of the SLAM positioning information node of the robot, the algorithm can search for the ideal result under the existing information, and the local optimization is performed to obtain the ideal result in another local state. Thus, the global accurate robot SLAM information is finally obtained. Simulation experiments show that the influence of the time delay parameter for simultaneous positioning of the robot SLAM is almost zero at different speeds, which shows the superior positioning stability of the new algorithm.
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2. Standard Particle Filter Slam Algorithm

The basic idea of the robot SLAM algorithm based on particle filter algorithm is as follows (Watanabe et al., 2017; Puyol et al., 2014). Assuming that the information IJGHPC.2020100106.m01 of mobile robot at t is a random sample N:


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