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Precedence-constrained path planning of messenger UAV for air-ground coordination

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Abstract

This paper addresses an unmanned aerial vehicle (UAV) path planning problem for a team of cooperating heterogeneous vehicles composed of one UAV and multiple unmanned ground vehicles (UGVs). The UGVs are used as mobile actuators and scattered in a large area. To achieve multi-UGV communication and collaboration, the UAV serves as a messenger to fly over all task points to collect the task information and then flies all UGVs to transmit the information about tasks and UGVs. The path planning of messenger UAV is formulated as a precedence-constrained dynamic Dubins traveling salesman problem with neighborhood (PDDTSPN). The goal of this problem is to find the shortest route enabling the UAV to fly over all task points and deliver information to all requested UGVs. When solving this path planning problem, a decoupling strategy is proposed to sequentially and rapidly determine the access sequence in which the UAV visits task points and UGVs as well as the access location of UAV in the communication neighborhood of each task point and each UGV. The effectiveness of the proposed approach is corroborated through computational experiments on randomly generated instances. The computational results on both small and large instances demonstrate that the proposed approach can generate high-quality solutions in a reasonable time as compared with two other heuristic algorithms.

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References

  1. M. Saska, V. Vonasek, T. Krajnik, et al. Coordination and navigation of heterogeneous MAV-UGV formations localized by a ‘hawk-eye’-like approach under a model predictive control scheme. International Journal of Robotics Research, 2014, 33(10): 1393–1412.

    Article  Google Scholar 

  2. J. Y. C. Chen. UAV-guided navigation for ground robot teleoperation in a military reconnaissance environment. Ergonomics, 2010, 53(8): 940–950.

    Article  Google Scholar 

  3. R. Bogue. The role of robots in the battlefields of the future. Industrial Robot, 2016, 43(4): 354–359.

    Article  Google Scholar 

  4. E. Garone, J. F. Determe, R. Naldi. Generalized traveling salesman problem for carrier-vehicle systems. Journal of Guidance Control and Dynamics, 2014, 37(3): 766–774.

    Article  Google Scholar 

  5. N. Mathew, S. L. Smith, S. L. Waslander. Planning paths for package delivery in heterogeneous multirobot teams. IEEE Transactions on Automation Science and Engineering, 2015, 12(4): 1298–1308.

    Article  Google Scholar 

  6. J. Chen, X. Zhang, B. Xin, et al. Coordination between unmanned aerial and ground vehicles: a taxonomy and optimization perspective. IEEE Transactions on Cybernetics, 2016, 46(4): 959–972.

    Article  Google Scholar 

  7. C. G. Cassandras, X. Lin, X. Ding. An optimal control approach to the multi-agent persistent monitoring problem. IEEE Transactions on Automatic Control, 2013, 58(4): 947–961.

    Article  MathSciNet  MATH  Google Scholar 

  8. B. Xin, Y. G. Zhu, Y. L. Ding, et al. Coordinated motion planning of multiple robots in multi-point dynamic aggregation task. Proceedings of the IEEE International Conference on Control and Automation, Nepal: IEEE, 2016: 933–938.

    Google Scholar 

  9. S. Lai, H. Qin, J. Q. Cui, et al. A robust online path planning approach in cluttered environments for micro rotorcraft drones. Control Theory and Technology, 2016, 14(1): 83–96.

    Article  MathSciNet  Google Scholar 

  10. P. Kolaric, C. Chen, A. Dalal, et al. Consensus controller for multi- UAV navigation. Control Theory and Technology, 2018, 16(2): 110–121.

    Article  MathSciNet  Google Scholar 

  11. B. Xin, J. Chen, D. L. Xu, et al. Hybrid encoding based differential evolution algorithms for Dubins traveling salesman problem with neighborhood. Control Theory and Applications, 2014, 31(7): 941–54.

    MATH  Google Scholar 

  12. J. T. Isaacs, D. J. Klein, J. P. Hespanha. Algorithms for the traveling salesman problem with neighborhoods involving a Dubins vehicle. Proceedings of the American Control Conference, New York: IEEE, 2011: 1704–1709.

    Google Scholar 

  13. Y. L. Ding, B. Xin, J. Chen, et al. Path planning of messenger UAV in air-ground coordination. The 20th World Congress of the International Federation of Automatic Control, Toulouse: IFAC Secretariat, 2017: 8045–8051.

    Google Scholar 

  14. L. E. Dubins. On curves of minimal length with a constraint on average curvature and with prescribed initial and terminal positions and tangents. American Journal of Mathematics, 1957, 79(3): 497–516.

    Article  MathSciNet  MATH  Google Scholar 

  15. P. Isaiah, T. Shima. Motion planning algorithms for the Dubin travelling salesperson problem. Automatica, 2015, 53(1): 247–255.

    Article  MathSciNet  MATH  Google Scholar 

  16. X. N. Bui, J. D. Boissonnat. Accessibility Region for A Car that Only Moves Forwards along Optimal Paths. Technical report. France: Institut national de recherche en informatique et en automatique, 1994: Research Report INRIA 2181.

    Google Scholar 

  17. X. Zhang, J. Chen, B. Xin, et al. A memetic algorithm for path planning of curvature-constrained UAVs performing surveillance of multiple ground targets. Chinese Journal of Aeronautics, 2014, 27(3): 622–633.

    Article  Google Scholar 

  18. F. Lokin. Procedures for travelling salesman problems with additional constraints. European Journal of Operational Research, 1979, 3(2): 135–141.

    Article  MATH  Google Scholar 

  19. Z. H. Ahmed. The ordered clustered travelling salesman problem: a hybrid genetic algorithm. Scientific World Journal, 2014: DOI 10.1155/2014/258207.

    Google Scholar 

  20. K. Helsgaun. An effective implementation of the lin-kernighan traveling salesman heuristic. European Journal of Operational Research, 2000, 126(1): 106–130.

    Article  MathSciNet  MATH  Google Scholar 

  21. X. Zhang, Y. Bai, B. Xin, et al. Differential evolution based receding horizon control for UAVmotion planning in dynamic environments. Jiqiren/Robot, 2013, 35(1): 107–114.

    Google Scholar 

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Authors and Affiliations

  1. School of Automation, Beijing Institute of Technology, Beijing, 100081, China

    Yulong Ding, Bin Xin & Jie Chen

  2. Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing Institute of Technology, Beijing, 100081, China

    Yulong Ding, Bin Xin & Jie Chen

  3. Beijing Advanced Innovation Center for Intelligent Robots and Systems, Beijing Institute of Technology, Beijing, 100081, China

    Bin Xin & Jie Chen

Authors
  1. Yulong Ding
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  2. Bin Xin
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  3. Jie Chen
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Corresponding author

Correspondence to Bin Xin.

Additional information

This work was supported in part by the National Outstanding Youth Talents Support Program (No. 61822304), in part by the National Natural Science Foundation of China (No. 61673058), in part by NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (No. U1609214), in part by the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (No. 61621063), in part by the Projects of Major International (Regional) Joint Research Program NSFC (No. 61720106011), and in part by International Graduate Exchange Program of Beijing Institute of Technology.

Yulong DING received the B.Sc. degree from Qilu University of Technology, Jinan, China, in 2012, and the M.Sc. degree from Xiamen University, Xiamen, China, in 2015. He is currently pursuing the Ph.D. degree with the School of Automation, Beijing Institute of Technology, Beijing. His current research interests include UAV-UGV collaborative systems, heterogeneous multi-agent systems, and task planning of multi-robot systems.

Bin XIN received the B.Sc. degree in Information Engineering and the Ph.D. degree in Control Science and Engineering, both from the Beijing Institute of Technology, Beijing, China, in 2004 and 2012, respectively. He was an academic visitor at the Decision and Cognitive Sciences Research Centre, the University of Manchester, from 2011 to 2012. He is currently an associate professor with the School of Automation, Beijing Institute of Technology. His current research interests include search and optimization, evolutionary computation, combinatorial optimization, and multi-agent systems. He is an Associate Editor of the Journal of Advanced Computational Intelligence and Intelligent Informatics and the journal Unmanned Systems. E-mail: brucebin@bit.edu.cn.

Jie CHEN received the B.Sc., M.Sc., and Ph.D. degrees in Control Theory and Control Engineering from the Beijing Institute of Technology, in 1986, 1996, and 2001, respectively. From 1989 to 1990, he was a visiting scholar in the California State University, U.S.A. From 1996 to 1997, he was a research fellow in the School of E&E, University of Birmingham, U.K. He is currently a professor of control science and engineering, the Beijing Institute of Technology, China. He is also an academician of the Chinese Academy of Engineering. He serves as a managing editor for the Journal of Systems Science and Complexity (2014-2017) and an associate editor for the IEEE Transactions on Cybernetics (2016-2018) and many other international journals. His main research interests include intelligent control and decision in complex systems, multi-agent systems, and optimization methods. He has co-authored 4 books and more than 200 research papers.

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Ding, Y., Xin, B. & Chen, J. Precedence-constrained path planning of messenger UAV for air-ground coordination. Control Theory Technol. 17, 13–23 (2019). https://doi.org/10.1007/s11768-019-8148-z

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  • DOI: https://doi.org/10.1007/s11768-019-8148-z

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