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Path Planning and Servo Tracking Control in Air-Ground Collaborative Unmanned System

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Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023) (ICAUS 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1174))

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Abstract

Air-Ground collaborative unmanned systems face challenges in communication, autonomous navigation, motion planning, and servo tracking control. This paper focuses on the path planning and servo tracking problems of a designed Air-Ground collaborative unmanned system consisting of an unmanned aerial vehicle (UAV) and an unmanned ground vehicle (UGV). A systematic function implementation framework is designed to realize the autonomous driving of the UGV in an unknown environment and servo tracking of the UAV to the UGV. The simultaneous localization and mapping (SLAM) technology is used to perform the mapping of the UGV. With map information, this paper introduces a path planner that satisfies the incomplete constraints and continuous state space of the UGV. Then, the UGV is controlled to track the planned path to a designated target given by the UAV. Considering two different application scenarios according to whether the position information can be obtained, two servo tracking controllers are proposed based on proportional differential (PD) and image-based visual servo (IBVS), respectively. Simulations are conducted to verify the feasibility and accuracy of the proposed approaches. The results show that the IBVS controller performs better than the PD controller in the system oscillation and reaction rate.

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References

  1. Chaimowicz, L.: Aerial shepherds: coordination among UAVs and swarms of robots. In: International Symposium on Distributed Autonomous Robotic Systems (2004)

    Google Scholar 

  2. Mueggler, E., Faessler, M., Fontana, F., et al.: Aerial-guided navigation of a ground robot among movable obstacles. In: 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 1–8. IEEE (2014)

    Google Scholar 

  3. Cao, S., Wang, X., Zhang, R., et al.: From demonstration to flight: realization of autonomous aerobatic maneuvers for fast, miniature fixed-wing UAVs. IEEE Robot. Autom. Lett. 7(2), 5771–5778 (2022)

    Article  Google Scholar 

  4. Zhang, H., Xin, B., Ding, Y.: Online path planning of messenger UAV in air-ground collaborative system. In: 2019 Chinese Control Conference (CCC), pp. 5875–5880. IEEE (2019)

    Google Scholar 

  5. Xiao, C., Zhao, X., Zou, Y., et al.: UAV multi-dynamic target points path planning with obstacles based on SOM-DAPF. In: 2020 Chinese Automation Congress (CAC), pp. 2301–2306. IEEE (2020)

    Google Scholar 

  6. Ren, S., Chen, Y., Xiong, L., et al.: Path planning for the marsupial double-UAVs system in air-ground collaborative application. In: 2018 37th Chinese Control Conference (CCC), pp. 5420–5425. IEEE (2018)

    Google Scholar 

  7. Peterson, J., Chaudhry, H., Abdelatty, K., et al.: Online aerial terrain mapping for ground robot navigation. Sensors 18(2), 630 (2018)

    Article  Google Scholar 

  8. Emirler, M.T., Uygan, İ.M.C., Aksun Güvenç, B., et al.: Robust PD steering control in parameter space for highly automated driving. Int. J. Veh. Technol. 2014 (2014)

    Google Scholar 

  9. Dolgov, D., Thrun, S., Montemerlo, M., et al.: Practical search techniques in path planning for autonomous driving. Ann Arbor 1001(48105), 18–80 (2008)

    Google Scholar 

  10. Hutchinson, S., Hager, G.D., Corke, P.I.: A tutorial on visual servo control. IEEE Trans. Robot. Autom. 12(5), 651–670 (1996)

    Article  Google Scholar 

  11. Rodriguez-Ramos, A., Sampedro, C., Bavle, H., et al.: A deep reinforcement learning strategy for UAV autonomous landing on a moving platform. J. Intell. Robot. Syst. 93, 351–366 (2019)

    Google Scholar 

  12. Falanga, D., Foehn, P., Lu, P., et al.: PAMPC: perception-aware model predictive control for quadrotors. In: 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1–8. IEEE (2018)

    Google Scholar 

  13. Yang, L., Liu, Z., Wang, X., et al.: An optimized image-based visual servo control for fixed-wing unmanned aerial vehicle target tracking with fixed camera. IEEE Access 7, 68455–68468 (2019)

    Article  Google Scholar 

  14. Yu, H., Meier, K., Argyle, M., Beard, R.W.: Cooperative path planning for target tracking in urban environments using unmanned air and ground vehicles. IEEE/ASME Trans. Mechatron. 20(2), 541–552 (2015)

    Google Scholar 

  15. Yu, H., Meier, K., Argyle, M., et al.: Cooperative path planning for target tracking in urban environments using unmanned air and ground vehicles. IEEE/ASME Trans. Mechatron. 20(2), 541–552 (2014)

    Article  Google Scholar 

  16. Reeds, J., Shepp, L.: Optimal paths for a car that goes both forwards and backwards. Pac. J. Math. 145(2), 367–393 (1990)

    Article  MathSciNet  Google Scholar 

  17. Kurzer, K.: Path planning in unstructured environments: a real-time hybrid a* implementation for fast and deterministic path generation for the kth research concept vehicle (2016)

    Google Scholar 

  18. Xiao, K., Tan, S., Wang, G., An, X., Wang, X., Wang, X.: XTDrone: a customizable multi-rotor UAVs simulation platform. In: 2020 4th International Conference on Robotics and Automation Sciences (ICRAS), pp. 55–61 (2020)

    Google Scholar 

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Correspondence to Huangchao Yu .

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Peng, Y., Yang, L., Yin, D., Yu, H., Wang, X. (2024). Path Planning and Servo Tracking Control in Air-Ground Collaborative Unmanned System. In: Qu, Y., Gu, M., Niu, Y., Fu, W. (eds) Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023). ICAUS 2023. Lecture Notes in Electrical Engineering, vol 1174. Springer, Singapore. https://doi.org/10.1007/978-981-97-1091-1_32

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