Reduction of Motion Data by Using Motion Assembly System for Haptic Database

Abstract

Recently, extensive research has been carried out on the preservation of human skill, a promising means of education and training. In the future, construction of motion database networks is required to preserve and utilize various skills. However, large-capacity data storage devices are required to save as many motion patterns as possible. Data compression methods based on signal processing are typically employed for data reduction. These methods, however, involve extensive and complex calculation and afford poor motion reproducibility. This paper presents a system for reducing motion data; this system has been designed without considering data compression methods. The proposed system is defined as a motion assembly system. During motion saving, the motion data measured by a master-slave system are saved and decomposed into a grasping mode and a manipulation mode. During motion reproduction, the data corresponding to the reproduced motion are generated by the assembly of the saved grasping and manipulation modes. Various motion patterns are reproduced by using some functional elements.

Clarification of Fundamental Motion Using Hierarchical Clustering and Graph Theory

“…A reduction method of motion data has been researched (8) . The literature (8) address a reduction method based on modal decomposition, and reduction of motion-data size was achieved.…”

“…The literature (8) address a reduction method based on modal decomposition, and reduction of motion-data size was achieved. However, fundamental motion data has to be clarified for motion reproduction when a robot having lower DOF than the robot in motion preservation is used.…”