An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning
Maritime activities have become increasingly frequent with the deepening of economic globalization, highlighting the burgeoning significance of maritime rescue. However, in practical applications, UAVs for maritime rescue face numerous challenges, such as limited endurance and inadequate autonomous...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/24/11816 |
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| author | Wenyuan Cong Hao Yi Feifan Yu Jiajie Chen Xinmin Chen Fengrui Xu |
| author_facet | Wenyuan Cong Hao Yi Feifan Yu Jiajie Chen Xinmin Chen Fengrui Xu |
| author_sort | Wenyuan Cong |
| collection | DOAJ |
| description | Maritime activities have become increasingly frequent with the deepening of economic globalization, highlighting the burgeoning significance of maritime rescue. However, in practical applications, UAVs for maritime rescue face numerous challenges, such as limited endurance and inadequate autonomous planning capabilities. To optimize flight routes and circumvent adverse sea conditions, an improved Pied Kingfisher Optimizer (IPKO) that incorporates refraction reverse learning, variable spiral search, and Cauchy mutation strategies was proposed. Comparative experiments conducted on CEC2005 and CEC2022 datasets with seven traditional algorithms demonstrate that the proposed algorithm exhibits superior precision and convergence speed. Subsequently, a path planning objective function was constructed based on trajectory cost and threat cost to simulate a 3D space for UAV maritime rescue missions, and the IPKO algorithm was applied to address the UAV path planning problem. The results showed that the total cost incurred by the IPKO algorithm decreased by 5.77% compared to the PKO algorithm and by 51.19% compared to the SCA algorithm. Finally, through UAV flight tests validating its practical applicability, it is ascertained that IPKO can enhance rescue efficiency in complex maritime rescue environments. |
| format | Article |
| id | doaj-art-0b98235cc7fb485da1034cfef55330e7 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-0b98235cc7fb485da1034cfef55330e72025-08-20T02:53:34ZengMDPI AGApplied Sciences2076-34172024-12-0114241181610.3390/app142411816An Improved Pied Kingfisher Optimizer for Maritime UAV Path PlanningWenyuan Cong0Hao Yi1Feifan Yu2Jiajie Chen3Xinmin Chen4Fengrui Xu5Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, ChinaFaculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo 315211, ChinaNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, ChinaNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, ChinaNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, ChinaNingbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences, Ningbo 315201, ChinaMaritime activities have become increasingly frequent with the deepening of economic globalization, highlighting the burgeoning significance of maritime rescue. However, in practical applications, UAVs for maritime rescue face numerous challenges, such as limited endurance and inadequate autonomous planning capabilities. To optimize flight routes and circumvent adverse sea conditions, an improved Pied Kingfisher Optimizer (IPKO) that incorporates refraction reverse learning, variable spiral search, and Cauchy mutation strategies was proposed. Comparative experiments conducted on CEC2005 and CEC2022 datasets with seven traditional algorithms demonstrate that the proposed algorithm exhibits superior precision and convergence speed. Subsequently, a path planning objective function was constructed based on trajectory cost and threat cost to simulate a 3D space for UAV maritime rescue missions, and the IPKO algorithm was applied to address the UAV path planning problem. The results showed that the total cost incurred by the IPKO algorithm decreased by 5.77% compared to the PKO algorithm and by 51.19% compared to the SCA algorithm. Finally, through UAV flight tests validating its practical applicability, it is ascertained that IPKO can enhance rescue efficiency in complex maritime rescue environments.https://www.mdpi.com/2076-3417/14/24/11816maritime search and rescuepath planningpied kingfisher optimizerintelligent transportation |
| spellingShingle | Wenyuan Cong Hao Yi Feifan Yu Jiajie Chen Xinmin Chen Fengrui Xu An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning Applied Sciences maritime search and rescue path planning pied kingfisher optimizer intelligent transportation |
| title | An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning |
| title_full | An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning |
| title_fullStr | An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning |
| title_full_unstemmed | An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning |
| title_short | An Improved Pied Kingfisher Optimizer for Maritime UAV Path Planning |
| title_sort | improved pied kingfisher optimizer for maritime uav path planning |
| topic | maritime search and rescue path planning pied kingfisher optimizer intelligent transportation |
| url | https://www.mdpi.com/2076-3417/14/24/11816 |
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