Use of support vector machines: Synergism to intelligent humanoid robot walking down on a slope

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4253 LNAI - III, Issue , 2006, Pages 670-676

  Kim, Dongwon ^a   Park, Gwi Tae ^a  

^a Korea University   (South Korea)

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT AGENTS; INTELLIGENT ROBOTS; MATHEMATICAL MODELS; MOTION ESTIMATION; NONLINEAR SYSTEMS; ROBOTICS;

HUMANOID ROBOT; SUPPORT VECTOR MACHINES (SVM); ZERO MOMENT POINT (ZMP);

LEARNING SYSTEMS;

EID: 33750714482     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11893011_85     Document Type: Conference Paper

References (7)

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2. Kim, D., Kim, N.H., Seo, S.J., Park, G.T.: Fuzzy Modeling of Zero Moment Point Trajectory for a Biped Walking Robot. Lect. Notes Artif. Int. 3214 (2005) 716-722
3. Kim, D., Seo, S.J., Park, G.T.: Zero-moment point trajectory modeling of a biped walking robot using an adaptive neuro-fuzzy systems. IEE Proc.-Control Theory Appl. 152 (2005) 411-426
4. Vapnik, V.: The Nature of Statistical Learning Theory. John Wiley. New York (1995)
5. Burges, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Mining Knowledge Discovery. 2 (1998) 121-167.
6. Oliveira, A.L.I.: Estimation of software project effort with support vector regression. Neurocomputing. (in press)
7. Gunn, S.: Support vector machines for classification and regression. ISIS technical report, Image Speech & Intelligent Systems Group University of Southampton (1998).