UAV Collision Avoidance in Unknown Scenarios with Causal Representation Disentanglement

UAV Collision Avoidance in Unknown Scenarios with Causal Representation Disentanglement

Deep reinforcement learning (DRL) has significantly advanced online path planning for unmanned aerial vehicles (UAVs). Nonetheless, DRL-based methods often encounter reduced performance when dealing with unfamiliar scenarios. This decline is mainly caused by the presence of non-causal and domain-spe...

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Bibliographic Details
Main Authors: Zhun Fan, Zihao Xia, Che Lin, Gaofei Han, Wenji Li, Dongliang Wang, Yindong Chen, Zhifeng Hao, Ruichu Cai, Jiafan Zhuang
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Drones
Subjects:
deep reinforcement learning
unmanned aerial vehicles
generalization capability
policy learning
causal representation disentanglement
Online Access:https://www.mdpi.com/2504-446X/9/1/10
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