Abstract
An algorithm for UAV collision avoidance based on the reinforcement learning is used for small fixed-wing unmanned aerial vehicles (UAVs). The proposed algorithm realized the obstacle avoidance of UAV in unknown environment and the result is close to the global optimal path. The simulation results show that the collision avoidance algorithm can adapt to various complex environments. Meanwhile, the UAV can quickly get close to the target while avoiding obstacles.
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Liu, J., Wang, Z., Zhang, Z. (2020). The Algorithm for UAV Obstacle Avoidance and Route Planning Based on Reinforcement Learning. In: Wang, R., Chen, Z., Zhang, W., Zhu, Q. (eds) Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019). Lecture Notes in Electrical Engineering, vol 582. Springer, Singapore. https://doi.org/10.1007/978-981-15-0474-7_70
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DOI: https://doi.org/10.1007/978-981-15-0474-7_70
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