Grasp Control Method for Robotic Manipulator Based on Federated Reinforcement Learning-Reference-Cited by-同舟云学术

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Grasp Control Method for Robotic Manipulator Based on Federated Reinforcement Learning

Published:2024-03-01 Issue: Volume:39 Page:1513-1519
ISSN:
Container-title:2024 7th International Conference on Advanced Algorithms and Control Engineering (ICAACE)
language:
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Author:

Wang Yue¹,Zhong Shida¹,Yuan Tao²

Affiliation:

1. College of Electronics and Information Engineering, Shenzhen University,State Key Laboratory of Radio Frequency Heterogeneous Integration,Shenzhen,China

2. Shenzhen University,Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication,Shenzhen,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10548022/10548040/10549724.pdf?arnumber=10549724

Reference21 articles.

1. Smart Manufacturing Scheduling With Edge Computing Using Multiclass Deep Q Network

2. Reinforcement learning of sensor-based reaching strategies for a two-link manipulator

3. Robotic Grasping using Deep Reinforcement Learning

4. Robot Grasping Based on RGB Object and Grasp Detection Using Deep Learning

5. Collaborative Pushing and Grasping of Tightly Stacked Objects via Deep Reinforcement Learning

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