An Improved Approach for Inverse Kinematics and Motion Planning of an Industrial Robot Manipulator with Reinforcement Learning
Author:
Affiliation:
1. Bochum University of Applied Sciences,Bochum,Germany
2. University of Applied Sciences Würzburg-Schweinfurt,Würzburg,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9699859/9699882/09699928.pdf?arnumber=9699928
Reference18 articles.
1. Manipulator Control Method Based on Deep Reinforcement Learning
2. A Reinforcement Learning Approach for Inverse Kinematics of Arm Robot
3. Motion Planning of Six-DOF Arm Robot Based on Improved DDPG Algorithm
4. A Kinematic Notation for Lower-Pair Mechanisms Based on Matrices
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1. Comparative Study of Machine Learning Techniques for Inverse Kinematics in a 5-DOF Manipulator;2023 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE);2023-11-08
2. Bayesian Optimization of Double-SAC Robotic Arm Path Planning Using Recent Prioritized Experience Replay;2023 WRC Symposium on Advanced Robotics and Automation (WRC SARA);2023-08-19
3. Generation and retrieval of procedural memory using natural intelligence for an articulated robot;2023 International Conference on IT Innovation and Knowledge Discovery (ITIKD);2023-03-08
4. Deep Reinforcement Learning for Robotic Control with Multi-Fidelity Models;IFAC PAPERSONLINE;2022
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