Deep reinforcement learning with domain randomization for overhead crane control with payload mass variations

Author:

Zhang Jianfeng,Zhao Chunhui,Ding Jinliang

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference41 articles.

1. A multi process value-based reinforcement learning environment framework for adaptive traffic signal control;Cao;Journal of Control and Decision,2022

2. A deep probabilistic transfer learning framework for soft sensor modeling with missing data;Chai;IEEE Transactions on Neural Networks and Learning Systems,2021

3. Understanding domain randomization for sim-to-real transfer;Chen,2022

4. Improving stochastic policy gradients in continuous control with deep reinforcement learning using the beta distribution;Chou,2017

5. Input shaping with an adaptive scheme for swing control of an underactuated tower crane under payload hoisting and mass variations;Fasih ur Rehman;Mechanical Systems and Signal Processing,2022

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1. Designing container crane control learning model using deep learning;Journal of Advanced Marine Engineering and Technology;2023-12-31

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