Copycat hand - robot hand generating imitative behavior

High speed, high accuracy and uniform processing time are essential in the hand posture estimation, to realize a robot hand capable of instantly imitating human actions. Therefore, in the present study, we have developed a method that enables the searching of similar images at high speeds and with high accuracy and the search involves uniform processing time, even in the case where a large-scale database is used. This is achieved by clustering databases having approximately uniform amounts of data using self-organization, including self-multiplication and self-extinction, and by collating the input images with the data in the database by means of the low-order image characteristics, while narrowing the search space in accordance with the past history. By estimating the sequential images of the finger shape by using this method, we successfully realized a process involving a joint angle estimation error within several degrees, a processing time of 150 - 160 fps, and an operating time without dispersion by using a PC having a CPU clock frequency of 2.8 GHz and a memory capacity of 512 MB.