舰船电子工程2025，Vol.45Issue(12)：36-40,5.DOI:10.3969/j.issn.1672-9730.2025.12.008
基于改进DDPG的无人船避障路径规划
Obstacle Avoidance Path Planning for Unmanned Ships Based on Improved DDPG
吴一凡 1李震 1王楠1
作者信息
- 1. 江苏科技大学海洋学院 镇江 212003
- 折叠
摘要
Abstract
In response to the problems of long training time,slow convergence,and poor performance in some complex situa-tions in deep reinforcement learning in dynamic environments,a combination of multi-step bootstrap,perturbation fluid algorithm(IFDS),and deep deterministic policy gradient algorithm(DDPG)is proposed.Firstly,N-step Bootstrap is added to DDPG to en-dow the model with the ability to combine multiple future time steps.Secondly,the perturbation fluid algorithm is introduced to joint-ly construct a potential field with the velocity information of obstacles in the environment,solving the problem of high-dimensional continuous action space and improving training efficiency.Finally,an environment consisting of a single obstacle and multiple obsta-cles is constructed to simulate and validate the algorithm.The simulation results show that the improved DDPG algorithm has higher training stability and speed compared to traditional DDPG algorithms in the simulation environment,and it can successfully achieve dynamic obstacle avoidance in more complex environments.At the same time,the success rate of training is improved.关键词
深度确定性策略梯度算法/多步自举/扰动流体算法/路径规划/无人船Key words
deep deterministic strategy gradient algorithm/multi-step bootstrapping/perturbation fluid algorithm/path planning/unmanned ship分类
信息技术与安全科学引用本文复制引用
吴一凡,李震,王楠..基于改进DDPG的无人船避障路径规划[J].舰船电子工程,2025,45(12):36-40,5.
