An Intelligent Collision Avoidance Algorithm for Unmanned Surface Vehicles Based on Deep Reinforcement Learning

Bowen Zu; Xiang Wang; Xuehua Zhou; Zhiguo Zhou

doi:10.1142/S2301385026500135

An Intelligent Collision Avoidance Algorithm for Unmanned Surface Vehicles Based on Deep Reinforcement Learning

Bowen Zu
, Xiang Wang
, Xuehua Zhou
, Zhiguo Zhou^*

^*此作品的通讯作者

Beijing Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

To address the obstacle avoidance challenge for unmanned surface vehicles, this paper presents a novel intelligent algorithm based on deep reinforcement learning. The algorithm incorporates human demonstration experience data for quick convergence and efficient decision-making. It features an end-to-end framework for multi-sensor data processing and immediate action decisions. Both simulation and deployment experiments evidence the superiority of this algorithm.

源语言	英语
页（从-至）	505-522
页数	18
期刊	Unmanned Systems
卷	14
期	2
DOI	https://doi.org/10.1142/S2301385026500135
出版状态	已出版 - 1 3月 2026
已对外发布	是

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title = "An Intelligent Collision Avoidance Algorithm for Unmanned Surface Vehicles Based on Deep Reinforcement Learning",

abstract = "To address the obstacle avoidance challenge for unmanned surface vehicles, this paper presents a novel intelligent algorithm based on deep reinforcement learning. The algorithm incorporates human demonstration experience data for quick convergence and efficient decision-making. It features an end-to-end framework for multi-sensor data processing and immediate action decisions. Both simulation and deployment experiments evidence the superiority of this algorithm.",

keywords = "Unmanned surface vehicles, artificial intelligence, deep reinforcement learning, obstacle avoidance",

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N2 - To address the obstacle avoidance challenge for unmanned surface vehicles, this paper presents a novel intelligent algorithm based on deep reinforcement learning. The algorithm incorporates human demonstration experience data for quick convergence and efficient decision-making. It features an end-to-end framework for multi-sensor data processing and immediate action decisions. Both simulation and deployment experiments evidence the superiority of this algorithm.

AB - To address the obstacle avoidance challenge for unmanned surface vehicles, this paper presents a novel intelligent algorithm based on deep reinforcement learning. The algorithm incorporates human demonstration experience data for quick convergence and efficient decision-making. It features an end-to-end framework for multi-sensor data processing and immediate action decisions. Both simulation and deployment experiments evidence the superiority of this algorithm.

KW - Unmanned surface vehicles

KW - artificial intelligence

KW - deep reinforcement learning

KW - obstacle avoidance

UR - https://www.scopus.com/pages/publications/105009138506

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An Intelligent Collision Avoidance Algorithm for Unmanned Surface Vehicles Based on Deep Reinforcement Learning

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