Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN
This study introduces an advanced automated guided vehicle (AGV) specifically designed for application in recirculating aquaculture systems (RASs). The proposed AGV seamlessly integrates automated feeding, real-time monitoring, and an intelligent path-planning system to enhance operational efficienc...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/9/7/476 |
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| author | Zhengjiang Guo Yingkai Xia Jiajun Liu Jian Gao Peng Wan Kan Xu |
| author_facet | Zhengjiang Guo Yingkai Xia Jiajun Liu Jian Gao Peng Wan Kan Xu |
| author_sort | Zhengjiang Guo |
| collection | DOAJ |
| description | This study introduces an advanced automated guided vehicle (AGV) specifically designed for application in recirculating aquaculture systems (RASs). The proposed AGV seamlessly integrates automated feeding, real-time monitoring, and an intelligent path-planning system to enhance operational efficiency. To achieve optimal and adaptive navigation, a hybrid algorithm is developed, incorporating Newton–Raphson-based optimisation (NRBO) alongside ant colony optimisation (ACO). Additionally, dueling deep Q-networks (dueling DQNs) dynamically optimise critical parameters, thereby improving the algorithm’s adaptability to the complexities of RAS environments. Both simulation-based and real-world experiments substantiate the system’s effectiveness, demonstrating superior convergence speed, path quality, and overall operational efficiency compared to traditional methods. The findings of this study highlight the potential of AGV to enhance precision and sustainability in recirculating aquaculture management. |
| format | Article |
| id | doaj-art-9bcb29c48e02478c95b513cb4b762214 |
| institution | DOAJ |
| issn | 2504-446X |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-9bcb29c48e02478c95b513cb4b7622142025-08-20T03:08:09ZengMDPI AGDrones2504-446X2025-07-019747610.3390/drones9070476Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQNZhengjiang Guo0Yingkai Xia1Jiajun Liu2Jian Gao3Peng Wan4Kan Xu5College of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaKey Laboratory of Aquaculture Facilities Engineering, Ministry of Agriculture and Rural Affairs, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaWuhan Second Ship Design and Research Institute, Wuhan 430205, ChinaThis study introduces an advanced automated guided vehicle (AGV) specifically designed for application in recirculating aquaculture systems (RASs). The proposed AGV seamlessly integrates automated feeding, real-time monitoring, and an intelligent path-planning system to enhance operational efficiency. To achieve optimal and adaptive navigation, a hybrid algorithm is developed, incorporating Newton–Raphson-based optimisation (NRBO) alongside ant colony optimisation (ACO). Additionally, dueling deep Q-networks (dueling DQNs) dynamically optimise critical parameters, thereby improving the algorithm’s adaptability to the complexities of RAS environments. Both simulation-based and real-world experiments substantiate the system’s effectiveness, demonstrating superior convergence speed, path quality, and overall operational efficiency compared to traditional methods. The findings of this study highlight the potential of AGV to enhance precision and sustainability in recirculating aquaculture management.https://www.mdpi.com/2504-446X/9/7/476recirculating aquaculture AGVpath planningNewton–Raphson-based optimiser (NRBO)ant colony optimisation (ACO)dueling deep Q-networks |
| spellingShingle | Zhengjiang Guo Yingkai Xia Jiajun Liu Jian Gao Peng Wan Kan Xu Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN Drones recirculating aquaculture AGV path planning Newton–Raphson-based optimiser (NRBO) ant colony optimisation (ACO) dueling deep Q-networks |
| title | Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN |
| title_full | Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN |
| title_fullStr | Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN |
| title_full_unstemmed | Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN |
| title_short | Path Planning Design and Experiment for a Recirculating Aquaculture AGV Based on Hybrid NRBO-ACO with Dueling DQN |
| title_sort | path planning design and experiment for a recirculating aquaculture agv based on hybrid nrbo aco with dueling dqn |
| topic | recirculating aquaculture AGV path planning Newton–Raphson-based optimiser (NRBO) ant colony optimisation (ACO) dueling deep Q-networks |
| url | https://www.mdpi.com/2504-446X/9/7/476 |
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