DocumentCode
2638890
Title
Motion simulation of robot arm using reinforcement learning
Author
Oshiro, Takahito ; Watanabe, Kajiro
Author_Institution
Hosei Univ., Tokyo
fYear
2007
fDate
17-20 Sept. 2007
Firstpage
1077
Lastpage
1080
Abstract
This paper describes the learning of robot arm action by reinforcement learning. We used Q-learning, which is a typical method of reinforcement learning, and which was programmed via MATLAB software. Simulations demonstrated the shortest path of robot arm motion to reach the target location.
Keywords
control engineering computing; learning (artificial intelligence); manipulators; MATLAB software; Q-learning; motion simulation; reinforcement learning; robot arm; Application software; Computer errors; Error correction; Learning; MATLAB; Manufacturing industries; Medical robotics; Medical simulation; Robot kinematics; Service robots; Q-learning; reinforcement learning; robot arm; simulation;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE, 2007 Annual Conference
Conference_Location
Takamatsu
Print_ISBN
978-4-907764-27-2
Electronic_ISBN
978-4-907764-27-2
Type
conf
DOI
10.1109/SICE.2007.4421144
Filename
4421144
Link To Document