Trajectory Generation for Multiprocess Robotic Tasks Based on Nested Dual-Memory Deep Deterministic Policy Gradient
Author:
Affiliation:
1. College of Information Science and Technology, Donghua University, Shanghai, China
Funder
Natural Science Foundation of Shanghai
Shanghai Rising-Star Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/3516/9985401/09756549.pdf?arnumber=9756549
Reference27 articles.
1. A General Framework of Motion Planning for Redundant Robot Manipulator Based on Deep Reinforcement Learning
2. Deep reinforcement learning for robotic pushing and picking in cluttered environment;deng;Proc IEEE Int Conf Intell Robot Syst,0
3. Learning Synergies Between Pushing and Grasping with Self-Supervised Deep Reinforcement Learning
4. Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning
5. Live Working Manipulator Control Model based on DPPO-DQN Combined Algorithm
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