Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles

Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles

The current unmanned surface vehicle (USV) intelligent obstacle avoidance algorithm based on deep reinforcement learning usually adopts the mass point model to train in an ideal environment. However, in actual navigation, due to the influence of the ship model and the water surface environment, the...

Full description

Saved in:
Bibliographic Details
Main Authors: Wangbin Luo, Xiang Wang, Fang Han, Zhiguo Zhou, Junyu Cai, Lin Zeng, Hong Chen, Jiawei Chen, Xuehua Zhou
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Journal of Marine Science and Engineering
Subjects:
USV
obstacle avoidance
deep reinforcement learning
proximal policy optimization
reward function
Online Access:https://www.mdpi.com/2077-1312/13/3/479
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/2077-1312/13/3/479

Similar Items