Abstract
Aiming at the autonomous collision avoidance problem for unmanned vehicles (UAVs) in low altitude environment, a novel decision mechanism based on 3D dynamic collision region is proposed in this paper. First, the models of collision avoidance are built, which relates to the UAV kinematic characteristics and the environment. Second, the 3D dynamic collision region is established, which contains the safety information of UAV relates to time and distance simultaneously. Besides, for the design of decision mechanism, the information given by the dynamic collision region is fully exploited and several novel definitions are proposed. Third, based on the safety criterions given by the dynamic collision region, a novel decision mechanism for collision avoidance is proposed. By choosing actions such as path re-planning and emergency maneuvers properly, the decision mechanism allows the UAV to better adapt to the complex environment and enhance the flight safety. Finally, simulations are carried out to verify the effectiveness of our proposed framework.
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References
Yu, X., Zhang, Y.: Sense and avoid technologies with applications to unmanned aircraft systems: review and prospects. Prog. Aerosp. Sci. 74, 152–166 (2015)
Barfield, F.: Autonomous collision avoidance: the technical requirements. In: National Aerospace and Electronics Conference 2000 on Proceedings of the IEEE 2000, pp. 808–813. IEEE (2000)
Rand, T.W., Eby, M.S.: Algorithms for airborne conflict detection, prevention, and resolution. In: The 23rd Digital Avionics Systems Conference, pp. 521–31. IEEE (2004)
Liu, C., Wang, H., Yao, P., Lei, Y.: Modeling and analysis of dynamic collision region for UAV avoiding aerial intruders. J. Beijing Univ. Aeronaut. Astronaut. 41(7), 1231–1238 (2015) (in Chinese)
Liu, X., Yang, X., Liu, Y., Yao, K.: UAV path planning based on GA-OCPA learning system. Acta. Aeronautica. et. Astronautica. Sinica. 38(11), 321275 (2017). (in Chinese)
Karaman, S., Frazzoli, E.: Linear temporal logic vehicle routing with applications to multi-UAV mission planning. Int. J. Roust. Nonlin. 21(12), 1372–1395 (2011)
Quintero, S.A.P., Papi, F., Klein, D.J., Chisci, L., Hespanha, J.P.: Optimal UAV coordination for target tracking using dynamic programming. In: 49th IEEE Conference on Decision and Control, pp. 4541–4546. IEEE (2010)
Koenig, S., Likhachev, M.: Real-time adaptive A In: Proceedings of the Fifth International Joint Conference on Autonomous Agents and Multiagent Systems, pp. 281–288. ACM (2006)
Szczerba, R.J., Galkowski, P.: Robust algorithm for real-time route planning. IEEE Trans. Aerosp. Electron. Syst. 36(3), 869–878 (2000)
Wu, J., Wang, H., Li, N., Yao, P., Huang, Y., Su, Z., Yu, Y.: Distributed trajectory optimization for multiple solar-powered UAVs target tracking in urban environment by Adaptive Grasshopper Optimization Algorithm. Aerosp. Sci. Technol. 70, 497–510 (2017)
Wu, J., Wang, H., Li, N., Yao, P., Huang, Y., Yang, H.: Path planning for solar-powered UAV in urban environment. Neurocomputing 275, 2055–2065 (2018)
Ge, S.S., Cui, Y.J.: New potential functions for mobile robot path planning. IEEE Trans. Robotic. Autom. 16(5), 615–620 (2000)
Wu, J., Wang, H., Li, N., Su, Z.: Formation obstacle avoidance: a fluid-based solution. IEEE. Syst. J. 14(1), 1479–1490 (2020)
Wu, J., Wang, H., Zhang, M.: Urban crowd surveillance in an emergency using unmanned air vehicles. J. Guid. Control. Dyn. (2020). https://doi.org/10.2514/1.g004088
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This work was supported by National Natural Science Foundation of China under Grants 61175084 and 61673042.
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Zhang, M., Wang, H., Wu, J. (2022). A Novel Autonomous Collision Avoidance Decision Mechanism for UAV in Low Altitude Environment Based on 3D Dynamic Collision Region. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_119
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DOI: https://doi.org/10.1007/978-981-15-8155-7_119
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