Study of Visual Servoing for Robot Hand Control

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In this research, we established a methodology for robot hand control by visual servoing technique, and constructed experimetnal system to verify its performances.As the research result, we present a general scheme to represent the relation between dynamic images and camera motion. We also propose its application to visual servoing.For a specific objects, whole combination of image data and camera position form the product space. The camera cannot obtain any arbitrary image, so that within this space the possible combination of the camera pose and the obtained image should be constrained on a lower dimensionla hyper surface. Our basic idea is that the visual servoing is interpreted as to find a path on this surface leading to a given goal image.Our approach is to analyze the properties of this surface, and utilize its differential or tangential property for vusual servoing. For this approach, the dimension of the image information becomes key problem. We propose to use the principal component analysis and to represent images with a composition of small number of "eigenimages" by using K-L (Karhunen-Loeve) expansion.In the report of the research, we describe, first, that a normal vector of this surface is related to the so-called Interation Matrix, and confirm the deasibility of our basic idea visual servoing with preliminary experiments. Then, we present a dynamical estimation of the normal vectors to move robot arm mouting a camera to a goal position where a given goal image will be obtained. We also consider the construction of the eigen space (the eigenimage space) to represent images efficietly and to speed-up convergence in the control. Experimental results of visual servoing with proposed method show the feasibility and applicability of our newly proposed approach.