Journal of System Simulation
Abstract
Abstract: Path planning is a key theoretical issue of the autonomous mobile robot technology. This paper utilizes an improved grid method to establish environment model, which involves a new priori advantage azimuth structure that includes two parts of the primary dominant grid cell and the subprime grid cell. It improves the pheromone mark ant colony optimization algorithm by putting forward a novel pheromone update strategy based on secondary path cognitive method, which is called bidirectional guidance strategies. It repeats an alternation of the starting point and the target point in each new round of iteration. The experimental results show that the improved algorithm has the advantages of low spatial complexity and high efficiency in solving large-scale planning problems especially with complex obstacles, and greatly improves the speed of initial solution construction and convergence, and has good solving performance.
Recommended Citation
Deng, Xiangyang; Zhang, Limin; Fang, Wei; and Tang, Miao
(2022)
"Robot Path Planning Based on Bidirectional Aggregation Ant Colony Optimization,"
Journal of System Simulation: Vol. 34:
Iss.
5, Article 16.
DOI: 10.16182/j.issn1004731x.joss.20-1000
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss5/16
First Page
1101
Revised Date
2021-11-24
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.20-1000
Last Page
1108
CLC
TP301.6;TP391.9
Recommended Citation
Xiangyang Deng, Limin Zhang, Wei Fang, Miao Tang. Robot Path Planning Based on Bidirectional Aggregation Ant Colony Optimization[J]. Journal of System Simulation, 2022, 34(5): 1101-1108.
DOI
10.16182/j.issn1004731x.joss.20-1000
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