Robot Path Planning Based on Bidirectional Aggregation Ant Colony Optimization

doi:10.16182/j.issn1004731x.joss.20-1000

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.

Key words: pheromone mark ant colony optimization (PM-ACO), bidirectional aggregation, robot path planning, node-based pheromone

CLC Number:

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.

Figures/Tables 7

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Table 1

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序号	最优值50×50		最优值首达轮次50×50		最优值80×80		最优值首达轮次80×80
序号	本文	文献[3]	本文	文献[3]	本文	文献[3]	本文	文献[3]
1	64	65	147	260	93	139	39	233
2	63	68	104	283	93	118	78	311
3	63	65	105	371	95	105	122	298
4	63	63	138	329	101	152	318	237
5	64	63	125	297	93	148	432	443
6	63	65	104	307	95	125	204	427
7	65	70	121	335	104	100	101	201
8	63	64	131	244	97	–	111	–
9	63	67	120	281	93	117	200	323
10	63	65	158	248	96	135	325	219
平均	63.4	65.5	125.3	295.5	96	126.6	193	299.1
最小	63	63	104	244	93	100	39	201
最大	65	70	158	377	104	152	432	443