Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning

Obstacle Avoidance for UAS in Continuous Action Space Using Deep Reinforcement Learning

Obstacle avoidance for small unmanned aircraft is vital for the safety of future urban air mobility (UAM) and Unmanned Aircraft System (UAS) Traffic Management (UTM). There are a variety of techniques for real-time robust drone guidance, but numerous of them solve in discretized airspace and control...

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Bibliographic Details
Main Authors: Jueming Hu, Xuxi Yang, Weichang Wang, Peng Wei, Lei Ying, Yongming Liu
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Continuous control
deep reinforcement learning
UAS obstacle avoidance
uncertainty
Online Access:https://ieeexplore.ieee.org/document/9868001/

Internet

https://ieeexplore.ieee.org/document/9868001/

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