Article

Communication-constrained task allocation of heterogeneous UAVs

  • CHEN Pu ,
  • YAN Fei ,
  • LIU Zhao ,
  • CHENG Guoda
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  • 1. AVIC Xi'an Flight Automatic Control Research Institute, Xi'an 710076, China;
    2. Chinese Flight Test Establishment, Xi'an 710089, China

Received date: 2021-04-15

  Revised date: 2021-05-08

  Online published: 2021-06-01

Abstract

When the heterogeneous multi-UAVs are performing the missions of cooperative reconnaissance and attack, there exists the problem of local task allocation under the constraints of communication distance and time delay. In this paper, a distributed multi-UAV task allocation method is proposed based on the contract net protocol. First, an optimization model of the local task allocation when heterogeneous multi-UAVs discover a new target is established. An information consensus algorithm is designed for the local UAV communication network to solve the conflict in the task announcement process. Then, a coalition formation and resource management method are proposed, so that the UAVs in the coalition can consume the resources in a more balanced way. Simulation results show that the proposed method can effectively solve the problem of task allocation of heterogeneous multi-UAV reconnaissance and attack mission under communication constraints, and can obtain the maximum system utility.

Cite this article

CHEN Pu , YAN Fei , LIU Zhao , CHENG Guoda . Communication-constrained task allocation of heterogeneous UAVs[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021 , 42(8) : 525844 -525844 . DOI: 10.7527/S1000-6893.2021.25844

References

[1] 姜霞, 曾宪琳, 孙健, 等. 多飞行器的分布式优化研究现状与展望[J]. 航空学报, 2021, 42(4):524551. JIANG X, ZENG X L, SUN J, et al. Research status and prospect of distributed optimization for multiple aircraft[J]. Acta Aeronautica et Astronautica Sinica, 2021, 42(4):524551(in Chinese).
[2] 王祥科, 刘志宏, 丛一睿, 等. 小型固定翼无人机集群综述和未来发展[J]. 航空学报, 2020, 41(4):023732. WANG X K, LIU Z H, CONG Y R, et al. Miniature fixed-wing UAV swarms:Review and outlook[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(4):023732(in Chinese).
[3] COUTINHO W P, BATTARRA M, FLIEGE J. The unmanned aerial vehicle routing and trajectory optimisation problem, a taxonomic review[J]. Computers & Industrial Engineering, 2018, 120:116-128.
[4] ZHAN C, ZENG Y. Aerial-ground cost tradeoff for multi-UAV-enabled data collection in wireless sensor networks[J]. IEEE Transactions on Communications, 2020, 68(3):1937-1950.
[5] DAI R, FOTEDAR S, RADMANESH M, et al. Quality-aware UAV coverage and path planning in geometrically complex environments[J]. Ad Hoc Networks, 2018, 73:95-105.
[6] ZHEN L, LI M, LAPORTE G, et al. A vehicle routing problem arising in unmanned aerial monitoring[J]. Computers & Operations Research, 2019, 105:1-11.
[7] SONG B D, KIM J, MORRISON J R. Rolling horizon path planning of an autonomous system of UAVs for persistent cooperative service:MILP formulation and efficient heuristics[J]. Journal of Intelligent & Robotic Systems, 2016, 84(1-4):241-258.
[8] XIONG C K, LU D, ZENG Z, et al. Path planning of multiple unmanned marine vehicles for adaptive ocean sampling using elite group-based evolutionary algorithms[J]. Journal of Intelligent & Robotic Systems, 2020, 99(3-4):875-889.
[9] JIA Z Y, YU J Q, AI X L, et al. Cooperative multiple task assignment problem with stochastic velocities and time windows for heterogeneous unmanned aerial vehicles using a genetic algorithm[J]. Aerospace Science and Technology, 2018, 76:112-125.
[10] WU W N, WANG X G, CUI N G. Fast and coupled solution for cooperative mission planning of multiple heterogeneous unmanned aerial vehicles[J]. Aerospace Science and Technology, 2018, 79:131-144.
[11] ZHU S R, ZHANG Y Z, GAO Y, et al. A cooperative task assignment method of multi-UAV based on self organizing map[C]//2018 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC). Piscataway:IEEE Press, 2018.
[12] STECZ W, GROMADA K. UAV mission planning with SAR application[J]. Sensors, 2020, 20(4):1080.
[13] BENADō G, HOOKER J N. Optimization bounds from the branching dual[J]. INFORMS Journal on Computing, 2020, 32(1):3-15.
[14] MARENDET A, GOLDSZTEJN A, CHABERT G, et al. A standard branch-and-bound approach for nonlinear semi-infinite problems[J]. European Journal of Operational Research, 2020, 282(2):438-452.
[15] VISWANATHAN S, RAVICHANDRAN K S, TAPAS A M, et al. An intelligent gain based ant colony optimisation method for path planning of unmanned ground vehicles[J]. Defence Science Journal, 2019, 69(2):167-172.
[16] WANG Z, LIU L, LONG T, et al. Multi-UAV reconnaissance task allocation for heterogeneous targets using an opposition-based genetic algorithm with double-chromosome encoding[J]. Chinese Journal of Aeronautics, 2018, 31(2):339-350.
[17] ARAFAT M Y, MOH S. Localization and clustering based on swarm intelligence in UAV networks for emergency communications[J]. IEEE Internet of Things Journal, 2019, 6(5):8958-8976.
[18] WU G H, PEDRYCZ W, LI H F, et al. Coordinated planning of heterogeneous earth observation resources[J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2016, 46(1):109-125.
[19] CHEN Y B, YANG D, YU J Q. Multi-UAV task assignment with parameter and time-sensitive uncertainties using modified two-part wolf pack search algorithm[J]. IEEE Transactions on Aerospace and Electronic Systems, 2018, 54(6):2853-2872.
[20] 郜晨, 何潇. 执行器饱和的多智能体一致性控制[J]. 航空学报, 2020, 41(S1):723760. GAO C, HE X. Consensus control for multi-agent systems subject to actuator saturations[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(S1):723760(in Chinese).
[21] ZHANG J R, WANG G, SONG Y F. Task assignment of the improved contract net protocol under a multi-agent system[J]. Algorithms, 2019, 12(4):70.
[22] BABEL L. Coordinated target assignment and UAV path planning with timing constraints[J]. Journal of Intelligent & Robotic Systems, 2019, 94(3-4):857-869.
[23] WANG Y, WANG S, TAN M, et al. Simultaneous arrival planning for multiple unmanned vehicles formation reconfiguration[J]. International Journal of Robotics and Automation, 2017, 32(4):360-8.
[24] SUJIT P B, MANATHARA J G, GHOSE D, et al. Decentralized multi-UAV coalition formation with limited communication ranges[M]//Handbook of Unmanned Aerial Vehicles, 2015:2021-2048.
[25] KIM M H, BAIK H, LEE S. Resource welfare based task allocation for UAV team with resource constraints[J]. Journal of Intelligent & Robotic Systems, 2015, 77(3-4):611-627.
[26] LADOSZ P, OH H, ZHENG G, et al. Gaussian process based channel prediction for communication-relay UAV in urban environments[J]. IEEE Transactions on Aerospace and Electronic Systems, 2020, 56(1):313-325.
[27] KIM K S, KIM H Y, CHOI H L. A bid-based grouping method for communication-efficient decentralized multi-UAV task allocation[J]. International Journal of Aeronautical and Space Sciences, 2020, 21(1):290-302.
[28] SHAO Z, YAN F, ZHOU Z, et al. Path planning for multi-UAV formation rendezvous based on distributed cooperative particle swarm optimization[J]. Applied Sciences, 2019, 9(13):2621.
[29] YAN F, ZHU X P, ZHOU Z, et al. A hierarchical mission planning method for simultaneous arrival of multi-UAV coalition[J]. Applied Sciences, 2019, 9(10):1986.
[30] YUAN Y P, SHEN X T, PAN W, et al. Constrained likelihood for reconstructing a directed acyclic Gaussian graph[J]. Biometrika, 2019, 106(1):109-125.
[31] SMITH R G. The contract net protocol:High-level communication and control in a distributed problem solver[J]. IEEE Transactions on Computers, 1980, 29(2):1104-1113.
[32] OWLIYA M, SAADAT M, JULES G G, et al. Agent-based interaction protocols and topologies for manufacturing task allocation[J]. IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2013, 43(1):38-52.
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