Integrated Design of Cooperative Area Coverage and Target Tracking with Multi-UAV System
Abstract
This paper systematically studies the cooperative area coverage and target tracking problem of multiple-unmanned aerial vehicles (multi-UAVs). The problem is solved by decomposing into three sub-problems: information fusion, task assignment, and multi-UAV behavior decision-making. Specifically, in the information fusion process, we use the maximum consistency protocol to update the joint estimation states of multi-targets (JESMT) and the area detection information. The area detection information is represented by the equivalent visiting time map (EVTM), which is built based on the detection probability and the actual visiting time of the area. Then, we model the task assignment problem of multi-UAV searching and tracking multi-targets as a network flow model with upper and lower flow bounds. An algorithm named task assignment minimum-cost maximum-flow (TAMM) is proposed. Cooperative behavior decision-making uses Fisher information as the mission reward to obtain the optimal tracking action of the UAV. Furthermore, a coverage behavior decision-making algorithm based on the anti-flocking method is designed for those UAVs assigned the coverage task. Finally, a distributed multi-UAV cooperative area coverage and target tracking algorithm is designed, which integrates information fusion, task assignment, and behavioral decision-making. Numerical and hardware-in-the-loop simulation results show that the proposed method can achieve persistent area coverage and cooperative target tracking.
References
[1]
Meng W, He Z, Teo R, Su R, and Xie L Integrated multi-agent system framework: Decentralised search, tasking and tracking IET Control Theory and Applications. 2015 9 493-502
[2]
Pimenta LCA, Schwager M, Lindsey Q, Kumar V, Rus D, Mesquita RC, and Pereira GAS Simultaneous Coverage and Tracking (SCAT) of Moving Targets with Robot Networks, 57, 85–99 2010 Berlin, Heidelberg Springer
[3]
Moon, S., Frew, E.W.: Distributed cooperative control for joint optimization of sensor coverage and target tracking. In: 2017 International Conference on Unmanned Aircraft Systems (ICUAS), 759–766 (2017)
[4]
Semnani SH and Basir OA Semi-flocking algorithm for motion control of mobile sensors in large-scale surveillance systems IEEE. Trans. Cybern. 2015 45 1 129-137
[5]
Meng W, He Z, Su R, Yadav PK, Teo R, and Xie L Decentralized multi-UAV flight autonomy for moving convoys search and track IEEE. Trans. Control. Syst. Technol. 2017 25 4 1480-1487
[6]
Yuan W, Ganganath N, Cheng C-T, Qing G, and Lau FCM Semiflocking-controlled mobile sensor networks for dynamic area coverage and multiple target tracking IEEE. Sens. J. 2018 18 21 8883-8892
[7]
Yuan, W., Ganganath, N., Cheng, C.-T., Valaee, S., Qing, G., Lau, F.C.M., Iu, H.H.C.: Semi-flocking-controlled mobile sensor networks for tracking targets with different priorities. In: 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 1–5 (2019)
[8]
Achanta S Passive target tracking using unscented kalman filter based on monte carlo simulation Indian. J. Sci. Technol. 2015 8 1-5
[9]
Lee, D.-y., Shim, S.-W., Hwang, M.-c., Tahk, M.-J.: Target tracking using adaptive coarse-to-fine particle filter. In: AIAA Guidance, Navigation, and Control Conference (2017)
[10]
Ren W, Beard RW, and Atkins EM Information consensus in multivehicle cooperative control IEEE. Control. Syst. Magazine. 2007 27 2 71-82
[11]
Yu D, Xia Y, Li L, and Zhu C Distributed consensus-based estimation with unknown inputs and random link failures Automatica. 2020 122
[12]
Fanti, M.P., Mangini, A.M., Ukovich, W.: A quantized consensus algorithm for distributed task assignment. In: 2012 IEEE Conference on Decision and Control (CDC), 2040–2045 (2012)
[13]
Luo L, Chakraborty N, and Sycara K Distributed algorithms for multirobot task assignment with task deadline constraints IEEE. Trans. Autom. Sci. Eng. 2015 12 3 876-888
[14]
Zhao Y, Wang X, Wang C, Cong Y, and Shen L Systemic design of distributed multi-uav cooperative decision-making for multi-target tracking Autonomous Agents and Multi-Agent Systems. 2019 33 132-158
[15]
Bänziger, T., Kunz, A., Wegener, K.: Optimizing human-robot task distribution using a simulation tool based on standardized work descriptions. J. Intell. Manuf. 31, 1635–1648 (2020)
[16]
Wu W and Nai-gang C Distributed task allocation for multiple heterogeneous uavs based on consensus algorithm and online cooperative strategy Aircraft Engineering and Aerospace Technology. 2018 90 9 1464-1473
[17]
Chen X, Zhang P, Du G, and Li F A distributed method for dynamic multi-robot task allocation problems with critical time constraints Robotics and Autonomous Systems. 2019 118 31-46
[18]
Dantzig G and Thapa M Network Flow Theory, 253–313 1997 New York, NY Springer
[19]
Li B, Springer J, Bebis G, and Gunes M A survey of network flow applications J. Netw. Comput. Appl. 2013 36 2 567-581
[20]
Marshall, J., Sun, W., L’Afflitto, A.: A survey of guidance, navigation, and control systems for autonomous multi-rotor small unmanned aerial systems. Annu. Rev. Control. 52, 390-427 (2021)
[21]
Zhu K, Han B, and Zhang T Multi-UAV distributed collaborative coverage for target search using heuristic strategy Guidance, Navigation and Control. 2021 01 1 2150002
[22]
Ni J, Tang G, Mo Z, Cao W, and Yang SX An improved potential game theory based method for multi-uav cooperative search IEEE Access. 2020 8 47787-47796
[23]
Chen, J., Du, C., Zhang, Y., Han, P., Wei, W.: A clustering-based coverage path planning method for autonomous heterogeneous uavs. IEEE Trans. Intell. Transp. Syst. 1–11 (2021)
[24]
Liu Z, Gao X, and Fu X A cooperative search and coverage algorithm with controllable revisit and connectivity maintenance for multiple unmanned aerial vehicles Sensors. 2018 18 5 1472
[25]
Ganganath N, Cheng C-T, and Tse CK Distributed antiflocking algorithms for dynamic coverage of mobile sensor networks IEEE. Trans. Ind. Inform. 2016 12 5 1795-1805
[26]
Ganganath N, Yuan W, Fernando T, Iu HHC, and Cheng C-T Energy-efficient anti-flocking control for mobile sensor networks on uneven terrains IEEE Transactions on Circuits and Systems II: Express Briefs. 2018 65 12 2022-2026
[27]
Zhang M and Liu H Cooperative tracking a moving target using multiple fixed-wing uavs J. Intell. Robotic. Syst. 2016 81 505-529
[28]
Zhou, X., Yi, Z., Liu, Y., Huang, K., Huang, H.: Survey on path and view planning for uavs. Virtual Reality & Intelligent Hardware. 2(1), 56–69 (2020)
[29]
Lu Y, Xue Z, Xia G-S, and Zhang L A survey on vision-based uav navigation Geo-spatial Information Science. 2018 21 1 21-32
[30]
Wang, X., Shen, L., Liu, Z., Zhao, S., Cong, Y., Li, Z., Jia, S., Chen, H., Yu, Y., Chang, Y., Wang, Y.: Coordinated flight control of miniature fixed-wing uav swarms: methods and experiments. Science China Information Sciences. 62(2019)
[31]
Chen H, Wang X, Shen L, and Yu Y Coordinated path following control of fixed-wing unmanned aerial vehicles in wind ISA Transactions. 2022 122 260-270
[32]
Zhao, S., Wang, X., Zhang, D., Shen, L.: Curved path following control for fixed-wing unmanned aerial vehicles with control constraint. J. Intell. Robotics Syst. 89(1–2), 107–119 (2018)
[33]
Monajemi Nejad, B., Attia, S., Raisch, J.: Max-consensus in a max-plus algebraic setting: The case of fixed communication topologies. 1–7 (2009)
[34]
Miao, Y.-Q., Khamis, A., Kamel, M.S.: Applying anti-flocking model in mobile surveillance systems. In: 2010 International Conference on Autonomous and Intelligent Systems, AIS 2010. 1–6 (2010)
[35]
Zhang, M., Li, H., Li, J., Wang, X.: A distributed persistent coverage algorithm of multiple unmanned aerial vehicles in complex mission areas. In: 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO). 1835–1840 (2021)
[36]
Chen H, Cong Y, Wang X, Xu X, and Shen L Coordinated pathfollowing control of fixed-wing unmanned aerial vehicles IEEE Transactions on Systems, Man, and Cybernetics: Systems. 2022 52 4 2540-2554
Index Terms
- Integrated Design of Cooperative Area Coverage and Target Tracking with Multi-UAV System
Index terms have been assigned to the content through auto-classification.
Recommendations
Multi-UAV airborne UV area coverage and task assignment method
AbstractTo address the area coverage problem in large-scale reconnaissance and detection tasks, Unmanned Aerial Vehicles(UAVs) utilize Ultraviolet(UV) light for flight guidance. Additionally, a UV light power control method is implemented to assist UAVs ...
Cooperative Tracking a Moving Target Using Multiple Fixed-wing UAVs
A cooperative tracking scheme is presented in this paper for multiple fixed-wing unmanned aerial vehicles (UAVs) to track an uncooperative, moving target. It is comprised of a target loitering algorithm and a formation flight algorithm. The loitering ...
Ground Target Tracking Control System for Unmanned Aerial Vehicles
The work here presented contributes to the development of ground target tracking control systems for fixed wing unmanned aerial vehicles (UAVs). The control laws are derived at the kinematic level, relying on a commercial inner loop controller onboard ...
Comments
Information & Contributors
Information
Published In
© The Author(s), under exclusive licence to Springer Nature B.V. 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Publisher
Kluwer Academic Publishers
United States
Publication History
Published: 04 August 2023
Accepted: 05 July 2023
Received: 25 November 2022
Author Tags
Qualifiers
- Research-article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 12 Nov 2024
Other Metrics
Citations
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in