DocumentCode :
1509216
Title :
Robot Learning in Practice [From the Guest Editors]
Author :
Morimoto, Jun
Volume :
17
Issue :
2
fYear :
2010
fDate :
6/1/2010 12:00:00 AM
Firstpage :
17
Lastpage :
18
Abstract :
Robotics researchers have made great efforts to model real environments in designing controllers. Thanks to the rapid increases in the computational speed of affordable computers and to the developments in sophisticated machine-learning algorithms, the acquisition of an environmental model and designing controllers from measured data with less prior information has become a practical approach. Work toward developing such robot-learning approaches can be expected to significantly contribute to the entire field of robotics research.
Keywords :
Algorithm design and analysis; Data mining; Hidden Markov models; Humanoid robots; Humans; Large-scale systems; Learning systems; Orbital robotics; Robot sensing systems; Velocity measurement;
fLanguage :
English
Journal_Title :
Robotics & Automation Magazine, IEEE
Publisher :
ieee
ISSN :
1070-9932
Type :
jour
DOI :
10.1109/MRA.2010.937374
Filename :
5480273
Link To Document :
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