Abstract
This paper improves the accuracy of a mine robot’s positioning and mapping for rapid rescue. Specifically, we improved the FastSLAM algorithm inspired by the lion swarm optimization method. Through the division of labor between different individuals in the lion swarm optimization algorithm, the optimized particle set distribution after importance sampling in the FastSLAM algorithm is realized. The particles are distributed in a high likelihood area, thereby solving the problem of particle weight degradation. Meanwhile, the diversity of particles is increased since the foraging methods between individuals in the lion swarm algorithm are different so that improving the accuracy of the robot’s positioning and mapping. The experimental results confirmed the improvement of the algorithm and the accuracy of the robot.
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
Reference33 articles.
1. Research and experiment of a new type of coal mine rescue robot;Hua;J. China Coal Soc.,2020
2. Research status of the disaster rescue robot and its applications to the mine rescue;Qian;Robot,2006
3. Classification system and key technology of coal mine robot;Ge;J. China Coal Soc.,2020
4. Simultaneous localization and mapping: part I
5. Optimization of the simultaneous localization and map-building algorithm for real-time implementation
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