DocumentCode :
1576841
Title :
Application of Reinforcement Learning to autonomous heading control for bionic underwater robots
Author :
Lin, Longxin ; Xie, Haibin ; Shen, Lincheng
Author_Institution :
Nat. Univ. of Defense Technol., Changsha, China
fYear :
2009
Firstpage :
2486
Lastpage :
2490
Abstract :
The bionic underwater robot propelled by undulating fins is an interesting field in current research on underwater robots. With the prosperous development of bionic underwater robots, its control problem remains big challenging for strong nonlinearity, uncertainty environments, and lack of understanding of dynamic characteristics of undulating fins. As a model-free method, the Q-learning based reinforcement learning achieves its control motivation by interacting with the environment and maximizing a reward, so suits the complicated applications such as robot control. This paper introduced the online Q_learning algorithm to the autonomous heading control for a kind of bionic underwater robot with two undulating fins. The algorithm doesn´t need to know any knowledge about the robot, and can learn the internal mapping between states and actions that control behaviors must contain. With the simulation experiments, the validity of reinforcement learning algorithm in autonomous heading control of the bionic underwater robot was validated.
Keywords :
biocybernetics; learning (artificial intelligence); marine systems; mobile robots; Q learning based reinforcement learning; autonomous heading control; bionic underwater robots; model free method; robot control; Biomimetics; Frequency; Learning; Marine animals; Propulsion; Robot control; Switches; Testing; Uncertainty; Vehicle dynamics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-4774-9
Electronic_ISBN :
978-1-4244-4775-6
Type :
conf
DOI :
10.1109/ROBIO.2009.5420445
Filename :
5420445
Link To Document :
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