Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA
In order to obtain an optimal trajectory for indoor AGV, this paper combined an improved ACO and fuzzy DWA (IACO-DWA) algorithm, which can provide an optimal path with collision-free under higher optimization efficiency. The highlights of this paper are detailed as follows: Firstly, an improved adap...
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AIMS Press
2023-10-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2023846?viewType=HTML |
| _version_ | 1797634003326468096 |
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| author | Zhen Zhou Chenchen Geng Buhu Qi Aiwen Meng Jinzhuang Xiao |
| author_facet | Zhen Zhou Chenchen Geng Buhu Qi Aiwen Meng Jinzhuang Xiao |
| author_sort | Zhen Zhou |
| collection | DOAJ |
| description | In order to obtain an optimal trajectory for indoor AGV, this paper combined an improved ACO and fuzzy DWA (IACO-DWA) algorithm, which can provide an optimal path with collision-free under higher optimization efficiency. The highlights of this paper are detailed as follows: Firstly, an improved adaptive pseudo-random transition strategy is adopted in the state transition probability with an angle factor. A reward and punishment mechanism is introduced in the pheromone updating strategy, then a path optimization strategy called IACO is proposed for the more optimized path. Secondly, IDWA adopted three fuzzy controllers of direction, security and adjustment coefficients through evaluating directional and safety principles, then improving the angular velocity by processing the linear velocity with linear normalization. By adapting to the changes of the environment, the IDWA parameters can be dynamically adjusted to ensure the optimal running speed and reasonable path of AGV. Thirdly, aiming to deal with the path-planning problem in complex environments, we combined IACO with IDWA, the hybrid algorithm involves dividing the globally optimal path obtained from IACO planning into multiple virtual sub-target points. IDWA completes the path planning by switching between these local target points, thereby improving the efficiency of the path planning. Finally, simulations is verified by Matlab and experiment results on the QBot2e platform are given to verify IACO-DWA algorithm's effectiveness and high performance. |
| first_indexed | 2024-03-11T12:01:42Z |
| format | Article |
| id | doaj.art-6d750763d4f54e30b6f5b3e85c42d707 |
| institution | Directory Open Access Journal |
| issn | 1551-0018 |
| language | English |
| last_indexed | 2024-03-11T12:01:42Z |
| publishDate | 2023-10-01 |
| publisher | AIMS Press |
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| series | Mathematical Biosciences and Engineering |
| spelling | doaj.art-6d750763d4f54e30b6f5b3e85c42d7072023-11-08T01:32:04ZengAIMS PressMathematical Biosciences and Engineering1551-00182023-10-012011191521917310.3934/mbe.2023846Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWAZhen Zhou 0Chenchen Geng1Buhu Qi2Aiwen Meng 3Jinzhuang Xiao4Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding 071000, ChinaKey Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding 071000, China Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding 071000, China Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding 071000, ChinaKey Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding 071000, ChinaIn order to obtain an optimal trajectory for indoor AGV, this paper combined an improved ACO and fuzzy DWA (IACO-DWA) algorithm, which can provide an optimal path with collision-free under higher optimization efficiency. The highlights of this paper are detailed as follows: Firstly, an improved adaptive pseudo-random transition strategy is adopted in the state transition probability with an angle factor. A reward and punishment mechanism is introduced in the pheromone updating strategy, then a path optimization strategy called IACO is proposed for the more optimized path. Secondly, IDWA adopted three fuzzy controllers of direction, security and adjustment coefficients through evaluating directional and safety principles, then improving the angular velocity by processing the linear velocity with linear normalization. By adapting to the changes of the environment, the IDWA parameters can be dynamically adjusted to ensure the optimal running speed and reasonable path of AGV. Thirdly, aiming to deal with the path-planning problem in complex environments, we combined IACO with IDWA, the hybrid algorithm involves dividing the globally optimal path obtained from IACO planning into multiple virtual sub-target points. IDWA completes the path planning by switching between these local target points, thereby improving the efficiency of the path planning. Finally, simulations is verified by Matlab and experiment results on the QBot2e platform are given to verify IACO-DWA algorithm's effectiveness and high performance.https://www.aimspress.com/article/doi/10.3934/mbe.2023846?viewType=HTMLant colony algorithmfuzzy controlglobal path planningagvdynamic window approach |
| spellingShingle | Zhen Zhou Chenchen Geng Buhu Qi Aiwen Meng Jinzhuang Xiao Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA Mathematical Biosciences and Engineering ant colony algorithm fuzzy control global path planning agv dynamic window approach |
| title | Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA |
| title_full | Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA |
| title_fullStr | Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA |
| title_full_unstemmed | Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA |
| title_short | Research and experiment on global path planning for indoor AGV via improved ACO and fuzzy DWA |
| title_sort | research and experiment on global path planning for indoor agv via improved aco and fuzzy dwa |
| topic | ant colony algorithm fuzzy control global path planning agv dynamic window approach |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2023846?viewType=HTML |
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