Sim-and-Real Reinforcement Learning for Manipulation: A Consensus-based Approach-Reference-Cited by-同舟云学术

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Sim-and-Real Reinforcement Learning for Manipulation: A Consensus-based Approach

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
language:
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Author:

Liu Wenxing¹,Niu Hanlin¹,Pan Wei²,Herrmann Guido³,Carrasco Joaquin³

Affiliation:

1. Remote Applications in Challenging Environments (RACE), United Kingdom Atomic Energy Authority,Culham,UK

2. The University of Manchester,the Department of Computer Science,Manchester,UK

3. The University of Manchester,the Department of Electrical & Electronic Engineering,Manchester,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10161062.pdf?arnumber=10161062

Reference36 articles.

1. Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics

2. V-REP: A versatile and scalable robot simulation framework

3. Learning a visuomotor controller for real world robotic grasping using simulated depth images;viereck;Conference on Robot Learning,2017

4. Human-level control through deep reinforcement learning

5. Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight

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1. Distributed Collision-Free Bearing Coordination of Multi-UAV Systems With Actuator Faults and Time Delays;IEEE Transactions on Intelligent Transportation Systems;2024-09

2. Consensus-based Deep Reinforcement Learning for Mobile Robot Mapless Navigation;2024 IEEE International Conference on Industrial Technology (ICIT);2024-03-25

3. Application of Multi Agent Reinforcement Learning to Robotic Pick and Place System;2024 10th International Conference on Automation, Robotics and Applications (ICARA);2024-02-22

4. Multiagent Hierarchical Reinforcement Learning With Asynchronous Termination Applied to Robotic Pick and Place;IEEE Access;2024

5. Sim-to-Real Deep Reinforcement Learning with Manipulators for Pick-and-Place;Towards Autonomous Robotic Systems;2023

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