Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster
This paper puts forward a joint optimization algorithm of task assignment and flight path planning for a heterogeneous unmanned aerial vehicle (UAV) cluster in a multi-mission scenario (MMS). The basis of the proposed algorithm is to establish constraint and threat models of a heterogeneous UAV clus...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/22/5315 |
| _version_ | 1797457879575298048 |
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| author | Xili Dong Chenguang Shi Wen Wen Jianjiang Zhou |
| author_facet | Xili Dong Chenguang Shi Wen Wen Jianjiang Zhou |
| author_sort | Xili Dong |
| collection | DOAJ |
| description | This paper puts forward a joint optimization algorithm of task assignment and flight path planning for a heterogeneous unmanned aerial vehicle (UAV) cluster in a multi-mission scenario (MMS). The basis of the proposed algorithm is to establish constraint and threat models of a heterogeneous UAV cluster to simultaneously minimize range and maximize value gain and survival probability in an MMS under the constraints of task payload, range, and task requirement. On one hand, the objective function for the heterogeneous UAV cluster within an MMS is derived and it is adopted as a metric for assessing the performance of the joint optimization in task assignment and flight path planning. On the other hand, since the formulated joint optimization problem is a multi-objective, non-linear, and non-convex optimization model due to its multiple decision variables and constraints, the roulette wheel selection (RWS) principle and the elite strategy (ES) are introduced in an ant colony optimization (ACO) to solve the complex optimization model. The simulation results indicate that the proposed algorithm is superior and more efficient compared to other approaches. |
| first_indexed | 2024-03-09T16:29:06Z |
| format | Article |
| id | doaj.art-144c0c194fd545f3a6629f99503235a8 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T16:29:06Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-144c0c194fd545f3a6629f99503235a82023-11-24T15:04:21ZengMDPI AGRemote Sensing2072-42922023-11-011522531510.3390/rs15225315Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV ClusterXili Dong0Chenguang Shi1Wen Wen2Jianjiang Zhou3Key Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Ministry of Education, Nanjing 210016, ChinaKey Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Ministry of Education, Nanjing 210016, ChinaKey Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Ministry of Education, Nanjing 210016, ChinaKey Laboratory of Radar Imaging and Microwave Photonics, Nanjing University of Aeronautics and Astronautics, Ministry of Education, Nanjing 210016, ChinaThis paper puts forward a joint optimization algorithm of task assignment and flight path planning for a heterogeneous unmanned aerial vehicle (UAV) cluster in a multi-mission scenario (MMS). The basis of the proposed algorithm is to establish constraint and threat models of a heterogeneous UAV cluster to simultaneously minimize range and maximize value gain and survival probability in an MMS under the constraints of task payload, range, and task requirement. On one hand, the objective function for the heterogeneous UAV cluster within an MMS is derived and it is adopted as a metric for assessing the performance of the joint optimization in task assignment and flight path planning. On the other hand, since the formulated joint optimization problem is a multi-objective, non-linear, and non-convex optimization model due to its multiple decision variables and constraints, the roulette wheel selection (RWS) principle and the elite strategy (ES) are introduced in an ant colony optimization (ACO) to solve the complex optimization model. The simulation results indicate that the proposed algorithm is superior and more efficient compared to other approaches.https://www.mdpi.com/2072-4292/15/22/5315multi-mission scenario (MMS)heterogeneous unmanned aerial vehicle (UAV) clustertask assignmentflight path planningjoint optimization methodsant colony optimization (ACO) |
| spellingShingle | Xili Dong Chenguang Shi Wen Wen Jianjiang Zhou Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster Remote Sensing multi-mission scenario (MMS) heterogeneous unmanned aerial vehicle (UAV) cluster task assignment flight path planning joint optimization methods ant colony optimization (ACO) |
| title | Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster |
| title_full | Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster |
| title_fullStr | Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster |
| title_full_unstemmed | Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster |
| title_short | Multi-Mission Oriented Joint Optimization of Task Assignment and Flight Path Planning for Heterogeneous UAV Cluster |
| title_sort | multi mission oriented joint optimization of task assignment and flight path planning for heterogeneous uav cluster |
| topic | multi-mission scenario (MMS) heterogeneous unmanned aerial vehicle (UAV) cluster task assignment flight path planning joint optimization methods ant colony optimization (ACO) |
| url | https://www.mdpi.com/2072-4292/15/22/5315 |
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