Title :
Optimizing Resolution for Feature Extraction in Robotic Motion Learning
Author :
Kato, Masato ; Kobayashi, Yuichi ; Hosoe, Shigeyuki
Author_Institution :
Nagoya Univ.
Abstract :
This paper presents a feature extraction method for robotic motion learning that optimizes image resolution to the task, thereby minimizing computation time. It utilizes mean-shift algorithms and principal component analysis for feature extraction, reinforcement learning for motion learning, and trial and error for finding the appropriate resolution. When applied to a manipulator pushing an object, the resolution adjustment method reduces the task time from one minute to 21 seconds
Keywords :
feature extraction; image motion analysis; image recognition; image resolution; learning (artificial intelligence); manipulators; optimisation; principal component analysis; robot vision; feature extraction; image recognition; image resolution optimization; manipulator; mean-shift algorithm; principal component analysis; reinforcement learning; resolution adjustment method; robotic motion learning; Cognitive robotics; Computational efficiency; Education; Feature extraction; Humans; Image processing; Image recognition; Image resolution; Learning; Robot motion; Feature extraction; image recognition; reinforcement learning;
Conference_Titel :
Systems, Man and Cybernetics, 2005 IEEE International Conference on
Conference_Location :
Waikoloa, HI
Print_ISBN :
0-7803-9298-1
DOI :
10.1109/ICSMC.2005.1571290
