Title :
Development of learning control in robots
Author :
Su, Hu ; De Xu ; Huang, Yanlong
Author_Institution :
State Key Lab. of Intell. Control & Manage. of Complex Syst., Chinese Acad. of Sci., Beijing, China
Abstract :
Learning control has been an active topic of research for several decades, and is of theoretical, as well as practical, significance. Current theories and developments in learning control are discussed. Following a brief introduction of the state as well as new progress on learning control, we give a detail review on the models and algorithms of the control policies developed recently which proved to be advantageous over previous approaches through experimental results. The related results and properties are presented. Then, several potentially developmental topics that are valuable to be further investigated are suggested. Finally, the conclusion remark is proposed.
Keywords :
learning (artificial intelligence); neurocontrollers; robots; active topic; control policy; learning control; robots; Data models; Heuristic algorithms; Hidden Markov models; Humans; Robot kinematics; Trajectory; Learning control; dynamic motor primitive; learn by imitation; locally weighted projection regress; locally weighted regress;
Conference_Titel :
Mechatronics and Automation (ICMA), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8113-2
DOI :
10.1109/ICMA.2011.5985697