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Reactive Obstacle Avoidance Method for a UAV

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Deep Learning for Unmanned Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 984))

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Abstract

Obstacle avoidance is very important for UAV flying in unknown environment. In this paper, the UAV’s obstacle avoidance method in unknown environment is proposed from two different view combined with the forward looking perception information of UAV. One is to propose a local real-time planning method from the perspective of optimization. The other is to combined with reinforcement learning to propose a method of avoiding action selection. In this paper, simulation experiments and comparative experiments are carried out to prove the effectiveness of the method.

This work was supported by National Nature Science Foundation (NNSF) of China under Grant 61876187.

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Author information

Authors and Affiliations

  1. College of Intelligence Science and Technology, National University of Defense Technology, Changsha, 410073, China

    Zhaowei Ma, Jia Hu, Yifeng Niu & Hongbo Yu

Authors
  1. Zhaowei Ma
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  2. Jia Hu
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  3. Yifeng Niu
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  4. Hongbo Yu
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Corresponding author

Correspondence to Yifeng Niu .

Editor information

Editors and Affiliations

  1. College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Anis Koubaa

  2. College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia

    Ahmad Taher Azar

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Ma, Z., Hu, J., Niu, Y., Yu, H. (2021). Reactive Obstacle Avoidance Method for a UAV. In: Koubaa, A., Azar, A.T. (eds) Deep Learning for Unmanned Systems. Studies in Computational Intelligence, vol 984. Springer, Cham. https://doi.org/10.1007/978-3-030-77939-9_3

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