Cooperation path planning of multi-UAV in road-network continuous monitoring

WANG Tong; HUANG Panfeng; DONG Gangqi

doi:10.7527/S1000-6893.2019.23753

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2020 , Vol. 41 >Issue S1: 723753 - 723753

DOI: https://doi.org/10.7527/S1000-6893.2019.23753

Cooperation path planning of multi-UAV in road-network continuous monitoring

WANG Tong ,
HUANG Panfeng ,
DONG Gangqi

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1. School of Astronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. National Key Laboratory of Aerospace Flight Dynamics, Northwestern Polytechnical University, Xi'an 710072, China

Received date: 2019-12-13

Revised date: 2019-12-25

Online published: 2019-12-26

Supported by

National Natural Science Foundation of China (61725303, 61803312)

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Abstract

In this paper, the problem of continuous monitoring of rotor UAVs in road-network environment is studied. Based on the optimization principle, the multi-UAVs road-network continuous monitoring problem is defined. By simplifying the discrete process for environment, considering the detection accuracy of sensors, and introducing uncertainty measurement, a model for road-network continuous monitoring is constructed. To address the particularity of path planning in continuous monitoring, a heuristic multi-UAVs cooperative path planning algorithm is designed. The theoretical analysis and simulation comparison verify the feasibility, accuracy, and generality of the proposed algorithm in multi-UAVs road-network continuous monitoring. As an extension of road-network patrolling method, this algorithm can not only provide a solution for the continuous monitoring task of road-network, but also be applied to the persistent data collection and continuous coverage tasks based on the graph model.

Key words： heuristic algorithm; multi-UAVs; cooperation; sensor coverage; road-network; continuous monitoring

Cite this article

WANG Tong , HUANG Panfeng , DONG Gangqi . Cooperation path planning of multi-UAV in road-network continuous monitoring[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020 , 41(S1) : 723753 -723753 . DOI: 10.7527/S1000-6893.2019.23753

References

[1] RASMUSSEN S, KALYANAM K, KINGSTON D. Field experiment of a fully autonomous multiple UAV/UGS intruder detection and monitoring system[C]//2016 International Conference on Unmanned Aircraft Systems (ICUAS), 2016.
[2] TROTTA A, FELICE M D, MONTORI F, et al. Joint coverage, connectivity, and charging strategies for distributed UAV networks[J]. IEEE Transactions on Robotics, 2018,34(4):883-900.
[3] GARCIA A P, ROLDAN J J, BARRIENTOS A. Monitoring traffic in future cities with aerial swarms:Developing and optimizing a behavior-based surveillance algorithm[J]. Cognitive Systems Research, 2019,54:273-286.
[4] ABBASI F, MESBAHI A, VELNI J M. A new voronoi-based blanket coverage control method for moving sensor networks[J]. IEEE Transactions on Control Systems Technology, 2019,27(1):409-417.
[5] ROLDAN J J, GARCIA A P, GARZON M, et al. Heterogeneous multi-robot system for mapping environmental variables of greenhouses[J]. Sensors, 2016,16(7):1018.
[6] KHAN A, RINNER B, CAVALLARO A. Cooperative robots to observe moving targets:Review[J]. IEEE Transactions on Cybernetics, 2018,48(1):187-198.
[7] KOLLING A, KLEINER A, CARPIN S. Coordinated search with multiple robots arranged in line formations[J]. IEEE Transactions on Robotics, 2018,34(2):459-473.
[8] THAKOOR O, GARG J, NAGI R. Multiagent UAV routing:A game theory analysis with tight price of anarchy bounds[J]. IEEE Transactions on Automation Science and Engineering, 2019, 17(11):1-17.
[9] NIGAM N, BIENIAWSKI S, KROO I, et al. Control of multiple UAVs for persistent surveillance:Algorithm and flight test results[J]. IEEE Transactions on Control Systems Technology, 2012,20(5):1236-1251.
[10] PASQUALETTI F, FRANCHI A, BULLO F. On cooperative patrolling:Optimal trajectories, complexity analysis, and approximation algorithms[J]. IEEE Transactions on Robotics, 2012,28(3):592-606.
[11] TOKEKAR P, HOOK J V, MULLA D, et al. Sensor planning for a symbiotic UAV and UGV system for precision agriculture[J]. IEEE Transactions on Robotics, 2016,32(6):1498-1511.
[12] PORTUGAL D, ROCHA R. A survey on multi-robot patrolling algorithms[M]. Berlin:Springer, 2011.
[13] ALAMDARI S, FATA E, SMITH S L. Persistent monitoring in discrete environments:Minimizing the maximum weighted latency between observations[J]. The International Journal of Robotics Research, 2014,33(1):138-154.
[14] YANOVSKI V, WAGNER I A, BRUCKSTEIN A M. A distributed ant algorithm for protect efficiently patrolling a network[J]. Algorithmica, 2003,37(3):165-186.
[15] CHEN H, CHENG T, WISE S. Developing an online cooperative police patrol routing strategy[J]. Computers, Environment and Urban Systems, 2017,62:19-29.
[16] PASQUALETTI F, DURHAM J W, BULLO F. Cooperative patrolling via weighted tours:Performance analysis and distributed algorithms[J]. IEEE Transactions on Robotics, 2012,28(5):1181-1188.
[17] CHEVALEYRE Y. Theoretical analysis of the multi-agent patrolling problem[C]//IEEE/WIC/ACM International Conference on Intelligent Agent Technology. Piscataway:IEEE Press, 2004.
[18] WIANDT B, SIMON V. Autonomous graph partitioning for multi-agent patrolling problems[C]//Federated Conference on Computer Science and Information Systems, 2018.
[19] CHEN H, CHENG T, YE X. Designing efficient and balanced police patrol districts on an urban street network[J]. International Journal of Geographical Information Science, 2019,33(2):269-290.
[20] TURNER J, MENG Q, SCHAEFER G, et al. Distributed task rescheduling with time constraints for the optimization of total task allocations in a multi-robot system[J]. IEEE Transactions on Cybernetics, 2018,48(9):2583-2597.
[21] ARSLAN O, KODITSCHEK D E. Sensor-based reactive navigation in unknown convex sphere worlds unknown convex sphere worlds[J]. The International Journal of Robotics Research, 2019,38(2-3):196-223.
[22] AZEVEDO S P, SILVA S R, NAZARIO R A. Reducing the range of perception in multi-agent patrolling strategies[J]. Journal of Intelligent & Robotic Systems, 2018,91(2):219-231.
[23] WAGNER I A, ALTSHULER Y, YANOVSKI V, et al. Cooperative cleaners:A study in ant robotics[J]. The International Journal of Robotics Research, 2008,27(1):127-151.
[24] PARK C, KIM Y, JEONG B. Heuristics for determining a patrol path of an unmanned combat vehicle[J]. Computers & Industrial Engineering, 2012,63(1):150-160.
[25] HOSHINO S, ISHIWATA T. Probabilistic surveillance by mobile robot for unknown intruders[C]//2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway:IEEE Press, 2015.
[26] CHEN S, WU F, SHEN L, et al. Decentralized patrolling under constraints in dynamic environments[J]. IEEE Transactions on Cybernetics, 2016,46(12):3364-3376.
[27] PORTUGAL D, ROCHA R P. Cooperative multi-robot patrol with Bayesian learning[J]. Autonomous Robots, 2016,40(5):929-953.
[28] PITA J, JAIN M, ORDONEZ F, et al. Using game theory for Los Angeles airport security[J]. AI Magazine, 2009,30(1):43-57.
[29] BOGERT K, DOSHI P. Multi-robot inverse reinforcement learning under occlusion with estimation of state transitions[J]. Artificial Intelligence, 2018,263:46-73.
[30] HUANG L, ZHOU M, HAO K, et al. A survey of multi-robot regular and adversarial patrolling[J]. IEEE/CAA Journal of Automatica Sinica, 2019,6(4):894-903.
[31] YU J, KARAMAN S, RUS D. Persistent monitoring of events with stochastic arrivals at multiple stations[J]. IEEE Transactions on Robotics, 2015,31(3):521-535.
[32] CHEN H, CHENG T, SHAWE T J. A balanced route design for min-max multiple-depot rural postman problem(MMMDRPP):A police patrolling case[J]. International Journal of Geographical Information Science, 2018,32(1):169-190.
[33] WALLAR A, PLAKU E, SOFGE D A. Reactive motion planning for unmanned aerial surveillance of risk-sensitive areas[J]. IEEE Transactions on Automation Science and Engineering, 2015,12(3):969-980.
[34] SRIVASTAVA V, PASQUALETTI F, BULLO F. Stochastic surveillance strategies for spatial quickest detection[J]. The International Journal of Robotics Research, 2013,32(12):1438-1458.
[35] NIGAM N. The multiple unmanned air vehicle persistent surveillance problem:A review[J]. Machines, 2014,2(1):13-69.

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