QR code

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...

Volledige beschrijving

Bewaard in:
Hoofdauteurs: Zhun Fan, Zihao Xia, Che Lin, Gaofei Han, Wenji Li, Dongliang Wang, Yindong Chen, Zhifeng Hao, Ruichu Cai, Jiafan Zhuang
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2024-12-01
Reeks:Drones
Onderwerpen:
deep reinforcement learning
unmanned aerial vehicles
generalization capability
policy learning
causal representation disentanglement
Online toegang:https://www.mdpi.com/2504-446X/9/1/10
Tags: Voeg label toe
Geen labels, Wees de eerste die dit record labelt!

Gelijkaardige items