Improved double DQN with deep reinforcement learning for UAV indoor autonomous obstacle avoidance

Abstract Aiming at the problems of insufficient autonomous obstacle avoidance performance of UAVs in complex indoor environments, an improved Double DQN algorithm based on deep reinforcement learning is proposed. The algorithm enhances the perception and learning capabilities by optimizing the netwo...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Ruiqi Yu, Qingdang Li, Jiewei Ji, Tingting Wu, Jian Mao, Shun Liu, Zhen Sun
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Subjects:
UAV
Indoor autonomous obstacle avoidance
Deep reinforcement learning
Double DQN algorithm
Dynamic exploration strategy
Online Access:https://doi.org/10.1038/s41598-025-02356-6

Internet

https://doi.org/10.1038/s41598-025-02356-6

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