Optimizing Resolution for Feature Extraction in Robotic Motion Learning

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… (More)
DOI: 10.1109/ICSMC.2005.1571290

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