Research on AUV Energy Saving 3D Path Planning with Mobility Constraints
This paper aims to focus on the path planning problem of AUV in the marine environment. As well as considering the path length and safe obstacle avoidance, ocean currents should not be ignored as the main factor affecting the navigation energy consumption of AUV. At the same time, the path should sa...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/10/6/821 |
| _version_ | 1797485721783631872 |
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| author | Guocheng Zhang Jixiao Liu Yushan Sun Xiangrui Ran Puxin Chai |
| author_facet | Guocheng Zhang Jixiao Liu Yushan Sun Xiangrui Ran Puxin Chai |
| author_sort | Guocheng Zhang |
| collection | DOAJ |
| description | This paper aims to focus on the path planning problem of AUV in the marine environment. As well as considering the path length and safe obstacle avoidance, ocean currents should not be ignored as the main factor affecting the navigation energy consumption of AUV. At the same time, the path should satisfy the mobility constraint of AUV; otherwise, the path is inaccessible to AUV. For the above problems, this paper presents a path planning algorithm based on an improved particle swarm (EPA-PSO); the fitness function is designed based on path length, energy consumption, and mobility constraints. The updated law of particle velocity and the initialization law of particles are improved, and the possible optimal solutions are stored in the feasible solution set; finally, the optimal solutions are obtained by comparison. The local jumping ability is given to the particle swarm so that the particles can jump out of the local optimal solution. The path planning simulation experiment is compared with the traditional PSO algorithm. The results show that the EPA-PSO algorithm proposed in this paper can be used in the AUV three-dimensional path planning process. It can effectively save energy and make the navigation path of AUV satisfy the requirements of maneuverability. The field experiment was completed in Shanghai, China, and the experiment proved that it was feasible to obtain a path satisfying the maneuverability constraints with optimal energy consumption for the problems studied in this paper. |
| first_indexed | 2024-03-09T23:22:55Z |
| format | Article |
| id | doaj.art-e3bdc1d2090b4574b5843d31e2c314e0 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-09T23:22:55Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-e3bdc1d2090b4574b5843d31e2c314e02023-11-23T17:23:30ZengMDPI AGJournal of Marine Science and Engineering2077-13122022-06-0110682110.3390/jmse10060821Research on AUV Energy Saving 3D Path Planning with Mobility ConstraintsGuocheng Zhang0Jixiao Liu1Yushan Sun2Xiangrui Ran3Puxin Chai4Laboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin 150001, ChinaLaboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin 150001, ChinaLaboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin 150001, ChinaLaboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin 150001, ChinaLaboratory of Science and Technology on Underwater Vehicle, Harbin Engineering University, Harbin 150001, ChinaThis paper aims to focus on the path planning problem of AUV in the marine environment. As well as considering the path length and safe obstacle avoidance, ocean currents should not be ignored as the main factor affecting the navigation energy consumption of AUV. At the same time, the path should satisfy the mobility constraint of AUV; otherwise, the path is inaccessible to AUV. For the above problems, this paper presents a path planning algorithm based on an improved particle swarm (EPA-PSO); the fitness function is designed based on path length, energy consumption, and mobility constraints. The updated law of particle velocity and the initialization law of particles are improved, and the possible optimal solutions are stored in the feasible solution set; finally, the optimal solutions are obtained by comparison. The local jumping ability is given to the particle swarm so that the particles can jump out of the local optimal solution. The path planning simulation experiment is compared with the traditional PSO algorithm. The results show that the EPA-PSO algorithm proposed in this paper can be used in the AUV three-dimensional path planning process. It can effectively save energy and make the navigation path of AUV satisfy the requirements of maneuverability. The field experiment was completed in Shanghai, China, and the experiment proved that it was feasible to obtain a path satisfying the maneuverability constraints with optimal energy consumption for the problems studied in this paper.https://www.mdpi.com/2077-1312/10/6/821autonomous underwater vehiclepath planningenergymobilityPSO |
| spellingShingle | Guocheng Zhang Jixiao Liu Yushan Sun Xiangrui Ran Puxin Chai Research on AUV Energy Saving 3D Path Planning with Mobility Constraints Journal of Marine Science and Engineering autonomous underwater vehicle path planning energy mobility PSO |
| title | Research on AUV Energy Saving 3D Path Planning with Mobility Constraints |
| title_full | Research on AUV Energy Saving 3D Path Planning with Mobility Constraints |
| title_fullStr | Research on AUV Energy Saving 3D Path Planning with Mobility Constraints |
| title_full_unstemmed | Research on AUV Energy Saving 3D Path Planning with Mobility Constraints |
| title_short | Research on AUV Energy Saving 3D Path Planning with Mobility Constraints |
| title_sort | research on auv energy saving 3d path planning with mobility constraints |
| topic | autonomous underwater vehicle path planning energy mobility PSO |
| url | https://www.mdpi.com/2077-1312/10/6/821 |
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