[1]XU Yuqiong,LOU Ke,LI Zhikun.Mobile robot path planning based on variable-step ant colony algorithm[J].CAAI Transactions on Intelligent Systems,2021,16(2):330-337.[doi:10.11992/tis.202004011]
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Mobile robot path planning based on variable-step ant colony algorithm

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 16 Number of periods: 2021 2 Page number: 330-337 Column: 学术论文—智能系统 Public date: 2021-03-05
Title:
Mobile robot path planning based on variable-step ant colony algorithm
Author(s):
XU Yuqiong1;  LOU Ke2;  LI Zhikun2; 3
1. Department of Electrical and Automotive Engineering, Songtian College, Guangzhou University, Guangzhou 511370, China;
2. Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment, Ministry of Education, Wuhu 241000, China;
3. Anhui Provincial Key Laboratory of Electric Transmission and Control, Anhui Polytechnic University, Wuhu 241000, China
Keywords:
traditional ant colony algorithm; double-layer ant colony algorithm; path planning; variable-step; pheromone; heuristic function; convergence; mobile robot
CLC:
TP242.6
DOI:
10.11992/tis.202004011
Abstract:
To address the problems of the traditional and double-layer ant colony algorithms, such as their low search efficiency, slow convergence, and high path–planning cost, in this paper we propose a variable-step ant colony algorithm. The proposed algorithm expands the set of mobile locations of the ant colony, and uses the variable-step strategy of selecting the hopping points, thus effectively shortening the path length of the mobile robot. The initialization pheromone adopts an uneven distribution, which increases the pheromone concentration of the grid in a straight line from the start to end points, with the pheromone decaying outward in parallel. The heuristic information matrix is improved and the method used to calculate the heuristic function of the mobile robot from the current to the end positions is adjusted. The experimental results show that the performance of the variable-step ant colony algorithm is superior to those of the double-layer and traditional ant colony algorithms with respect to path length and convergence speed, which proves its effectiveness and superiority. Thus, the proposed algorithm is effective in solving the path-planning problem of mobile robots.
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Last Update: 2021-04-25

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