Path Planning Based on Deep Reinforcement Learning for Autonomous Underwater Vehicles Under Ocean Current Disturbance-Reference-Cited by-同舟云学术

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Path Planning Based on Deep Reinforcement Learning for Autonomous Underwater Vehicles Under Ocean Current Disturbance

Published:2023-01 Issue:1 Volume:8 Page:108-120
ISSN:2379-8904
Container-title:IEEE Transactions on Intelligent Vehicles
language:
Short-container-title:IEEE Trans. Intell. Veh.

Author:

Chu Zhenzhong¹^ORCID,Wang Fulun²^ORCID,Lei Tingjun³^ORCID,Luo Chaomin³^ORCID

Affiliation:

1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai, China

2. Information Engineering College, Shanghai Maritime University, Shanghai, China

3. Department of Electrical and Computer Engineering, Mississippi State University, Mississippi State, MS, USA

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Control and Optimization,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/7274857/10024686/09722969.pdf?arnumber=9722969

Reference53 articles.

1. Deep Distributional Reinforcement Learning Based High-Level Driving Policy Determination

2. Trajectory Planning for Navigation Aiding of Autonomous Underwater Vehicles

3. Neural-network estimators based fault-tolerant tracking control for AUV via ADP with rudders faults and ocean current disturbance

4. Manipulation and Transportation With Cooperative Underwater Vehicle Manipulator Systems

5. Optimal path planning approach based on Q-learning algorithm for mobile robots

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