ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Path planning for AUV&UAV cross⁃domain collaborative search and tracking
Received date: 2023-01-03
Revised date: 2023-04-10
Accepted date: 2023-05-07
Online published: 2023-05-12
Supported by
National Nature Science Foundation of China(51909206);China Postdoctoral Science Foundation(2021M692616);Natural Science Basic Research Plan in Shaanxi Province of China(2019JQ-607);Zhejiang Provincial Natural Science Foundation of China(LQ20E090010);Fundamental Research Funds for the Central Universities(31020200QD044)
It is an important part for maintaining marine homeland security to detect unknown targets in the offshore area in time and track and identify them. Cross-domain collaborative search of unmanned platforms has been widely applied to military and civilian tasks. In this paper， Autonomous Underwater Vehicle （AUV） and Unmanned Aerial Vehicle （UAV） are used to perform the search and tracking tasks of underwater targets in offshore areas. The whole task process can be divided into two stages： target search and target tracking. The objective of the two stages is to maximize the total search space and minimize the end position error between AUV and underwater targets， respectively. Firstly， the search and tracking tasks are described， and the cross-domain collaborative search model of AUV&UAV is established. Secondly， various constraints such as navigation ability， detection distance and communication range in the cross-domain collaborative search model are set. Finally， in the cross-domain collaborative search and tracking planning， based on the improved genetic algorithm and the asynchronous planning strategy， the search and tracking paths are generated by centralized and distributed decision-making respectively. The simulation results show that the AUV&UAV cross-domain unmanned system can complete the underwater target search and tracking tasks under different conditions.
Wenjun DING , Yajun CHAI , Dongdong HOU , Chiyu WANG , Guozong ZHANG , Zhaoyong MAO . Path planning for AUV&UAV cross⁃domain collaborative search and tracking[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2023 , 44(21) : 528471 -528471 . DOI: 10.7527/S1000-6893.2023.28471
| 1 | 张哲璇， 龙腾， 徐广通， 等. 重访机制驱动的多无人机协同动目标搜索方法［J］. 航空学报， 2020， 41（5）： 323314. |
| ZHANG Z X， LONG T， XU G T， et al. Revisit mechanism driven multi-UAV cooperative search planning method for moving targets［J］. Acta Aeronautica et Astronautica Sinica， 2020， 41（5）： 323314 （in Chinese）. | |
| 2 | 熊伟， 朱洪峰， 崔亚奇. 在线学习的循环自适应机动目标跟踪算法［J］. 航空学报， 2022， 43（5）： 325250. |
| XIONG W， ZHU H F， CUI Y Q. Recurrent adaptive maneuvering target tracking algorithm based on online learning［J］. Acta Aeronautica et Astronautica Sinica， 2022， 43（5）： 325250 （in Chinese）. | |
| 3 | 陈军， 张新伟， 徐嘉， 等. 有人/无人机混合编队有限干预式协同决策［J］. 航空学报， 2015， 36（11）： 3652-3665. |
| CHEN J， ZHANG X W， XU J， et al. Human/unmanned-aerial-vehicle team collaborative decision-making with limited intervention［J］. Acta Aeronautica et Astronautica Sinica， 2015， 36（11）： 3652-3665 （in Chinese）. | |
| 4 | 胡腾， 刘占军， 刘洋， 等. 多无人机3D侦察路径规划［J］. 系统工程与电子技术， 2019， 41（7）： 1551-1559. |
| HU T， LIU Z J， LIU Y， et al. 3D surveillance path planning for multi-UAVs［J］. Systems Engineering and Electronics， 2019， 41（7）： 1551-1559 （in Chinese）. | |
| 5 | 李绍斌， 姜大立， 杨西龙， 等. 基于混合遗传算法的多基地多无人机战场物资配送任务分配［J］. 装甲兵工程学院学报， 2019， 33（2）： 10-19. |
| LI S B， JIANG D L， YANG X L， et al. Multi-base and multi-UAV battlefield material distribution task assignment based on hybrid genetic algorithm［J］. Journal of Academy of Armored Force Engineering， 2019， 33（2）： 10-19 （in Chinese）. | |
| 6 | QIE T Q， WANG W D， YANG C， et al. A path planning algorithm for autonomous flying vehicles in cross-country environments with a novel TF-RRT* method［J］. Green Energy and Intelligent Transportation， 2022， 1（3）： 100026. |
| 7 | 杨勇， 丁勇， 黄鑫城. 改进APF与Bezier相结合的多无人机协同避碰航路规划［J］. 电光与控制， 2018， 25（11）： 36-41. |
| YANG Y， DING Y， HUANG X C. Multi-UAV cooperative collision avoidance route planning based on improved artificial potential field and Bezier curve［J］. Electronics Optics & Control， 2018， 25（11）： 36-41 （in Chinese）. | |
| 8 | 包昕幼. 浅水区域无人探测艇编队巡航路径规划研究［D］. 广州： 华南理工大学， 2018. |
| BAO X Y. Study on cruise route planning of unmanned exploration vessel formation in shallow water area［D］. Guangzhou： South China University of Technology， 2018 （in Chinese）. | |
| 9 | HE S D， WANG M， DAI S L， et al. Leader-follower formation control of USVs with prescribed performance and collision avoidance［J］. IEEE Transactions on Industrial Informatics， 2019， 15（1）： 572-581. |
| 10 | DAI S L， HE S D， LIN H， et al. Platoon formation control with prescribed performance guarantees for USVs［J］. IEEE Transactions on Industrial Electronics， 2018， 65（5）： 4237-4246. |
| 11 | HAN G J， LONG X H， ZHU C， et al. A high-availability data collection scheme based on multi-AUVs for underwater sensor networks［J］. IEEE Transactions on Mobile Computing， 2020， 19（5）： 1010-1022. |
| 12 | 马朋， 张福斌， 徐德民. 基于距离量测的双领航多AUV协同定位队形优化分析［J］. 控制与决策， 2018， 33（2）： 256-262. |
| MA P， ZHANG F B， XU D M. Optimality analysis for formation of MAUV cooperative localization with two leaders based on range measurements［J］. Control and Decision， 2018， 33（2）： 256-262 （in Chinese）. | |
| 13 | RIDAO P， CARRERAS M， RIBAS D， et al. Intervention AUVs： The next challenge［J］. Annual Reviews in Control， 2015， 40： 227-241. |
| 14 | NI J J， YANG L， WU L Y， et al. An improved spinal neural system-based approach for heterogeneous AUVs cooperative hunting［J］. International Journal of Fuzzy Systems， 2018， 20（2）： 672-686. |
| 15 | QIN H L， MENG Z H， MENG W， et al. Autonomous exploration and mapping system using heterogeneous UAVs and UGVs in GPS-denied environments［J］. IEEE Transactions on Vehicular Technology， 2019， 68（2）： 1339-1350. |
| 16 | BELLA S， BELBACHIR A， BELALEM G. A centralized autonomous system of cooperation for UAVs-monitoring and USVs-cleaning［M］∥ Unmanned Aerial Vehicles. Hershey： IGI Global， 2019： 347-375. |
| 17 | BELLA S， BELBACHIR A， BELALEM G. A hybrid architecture for cooperative UAV and USV swarm vehicles［C］∥ International Conference on Machine Learning for Networking. Cham： Springer， 2019： 341-363. |
| 18 | LI Y， MA T， CHEN P Y， et al. Autonomous underwater vehicle optimal path planning method for seabed terrain matching navigation［J］. Ocean Engineering， 2017， 133： 107-115. |
| 19 | SHEN C， SHI Y， BUCKHAM B. Integrated path planning and tracking control of an AUV： A unified receding horizon optimization approach［J］. IEEE/ASME Transactions on Mechatronics， 2017， 22（3）： 1163-1173. |
| 20 | CUI R X， LI Y， YAN W S. Mutual information-based multi-AUV path planning for scalar field sampling using multidimensional RRT* ［J］. IEEE Transactions on Systems， Man， and Cybernetics： Systems， 2016， 46（7）： 993-1004. |
| 21 | WU Y. Coordinated path planning for an unmanned aerial-aquatic vehicle （UAAV） and an autonomous underwater vehicle （AUV） in an underwater target strike mission［J］. Ocean Engineering， 2019， 182： 162-173. |
| 22 | ZHANG H， LIU C， ZHAO W Z. Segmented trajectory planning strategy for active collision avoidance system［J］. Green Energy and Intelligent Transportation， 2022， 1（1）： 100002. |
| 23 | 韩凯， 董日昌， 邵丰伟， 等. 基于改进遗传算法的导航卫星星间链路网络动态拓扑优化技术［J］. 航空学报， 2022， 43（9）： 326095. |
| HAN K， DONG R C， SHAO F W， et al. Dynamic topology optimization of navigation satellite inter-satellite links network based on improved genetic algorithm［J］. Acta Aeronautica et Astronautica Sinica， 2022， 43（9）： 326095 （in Chinese）. | |
| 24 | 赵鹏程， 宋保维， 毛昭勇， 等. 基于改进的复合自适应遗传算法的UUV水下回收路径规划［J］. 兵工学报， 2022， 43（10）： 2598-2608. |
| ZHAO P C， SONG B W， MAO Z Y， et al. Path planning for UUV underwater recovery based on improved composite adaptive genetic algorithm［J］. Acta Armamentarii， 2022， 43（10）： 2598-2608 （in Chinese）. | |
| 25 | WU Y， LOW K H， LV C. Cooperative path planning for heterogeneous unmanned vehicles in a search-and-track mission aiming at an underwater target［J］. IEEE Transactions on Vehicular Technology， 2020， 69（6）： 6782-6787. |
| 26 | 吴宇， 苏析超， 崔佳鹏， 等. USV&AUV水下目标协同搜索与打击航迹规划［J］. 控制与决策， 2021， 36（4）： 825-834. |
| WU Y， SU X C， CUI J P， et al. Coordinated path planning of USV & AUV for an underwater target［J］. Control and Decision， 2021， 36（4）： 825-834 （in Chinese）. |
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