Abstract
The path planning and control of unmanned aerial vehicles (UAVs) is an important part of autonomous flight. High-precision positioning and navigation is one of the key technologies to achieve adaptive flight, efficient reconnaissance and precise attack. A control method of adaptive target tracking and obstacle avoidance for rotorcraft UAVs is proposed in the paper to solve the problem. According to the characteristics of the nonlinear UAVs’ system, the artificial potential field method and backstepping method are used for path planning and flight control respectively. The unscented Kalman filter combined with UWB and INS is used to obtain accurate position and feedback to the artificial potential field to ensure the stability of the system and the accuracy of target tracking. This paper describes the dynamic target simulation of multiple obstacles. It is shown that the satisfactory tracking performance with the new algorithm, and the stability of obstacle avoidance is also improved.
This research was supported by the Opening Project of Unmanned System Intelligent Perception Control Technology Engineering Laboratory of Sichuan Province(WRXT2021-004).
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Liu, P. et al. (2023). Research on UAV Dynamic Target Tracking with Multi-sensor Position Feedback. In: Tan, Y., Shi, Y., Luo, W. (eds) Advances in Swarm Intelligence. ICSI 2023. Lecture Notes in Computer Science, vol 13969. Springer, Cham. https://doi.org/10.1007/978-3-031-36625-3_8
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