Title :
Application of SVM in intelligent robot information acquisition and processing: a survey
Author :
Lei, Jianhe ; Song, Quanjun ; Ma, Jinghua ; Qiu, LianKui ; Ge, Yunjian
Author_Institution :
Inst. of Intelligent Machines, Chinese Acad. of Sci.,, Anhui, China
fDate :
27 June-3 July 2005
Abstract :
SVM (support vector machines) is a new machine learning technique developed on statistical learning theory and has attracted more and more attentions. For machine learning tasks involving pattern classification, multi sensors information fusion, non-linear system control, etc, SVMs have become increasingly popular tools. In this paper, we survey the recent new development on the research and application of SVM in intelligent robot information acquisition and processing. Some important issues and the directions of further research are pointed out also.
Keywords :
data acquisition; intelligent robots; learning (artificial intelligence); sensor fusion; statistical analysis; support vector machines; SVM; intelligent robot information acquisition; intelligent robot information processing; machine learning technique; multisensor information fusion; statistical learning theory; support vector machine; Intelligent robots; Intelligent sensors; Machine learning; Nonlinear control systems; Pattern classification; Sensor fusion; Sensor systems; Statistical learning; Support vector machine classification; Support vector machines;
Conference_Titel :
Information Acquisition, 2005 IEEE International Conference on
Print_ISBN :
0-7803-9303-1
DOI :
10.1109/ICIA.2005.1635077
