Direct Interpretation of Dynamic Images and Camera Motion for Visual Servoing Without Image Feature Correspondence

摘要

A general scheme to represent the relation between dynamic images and camera motion is presented. Then its application to visual servoing is proposed. For a specific object, every possible combination of the camera pose and the obtained image should be constrained on a lower dimensional hyper surface in the product space of the whole combination of image data and camera position. Visual servoing, for example, is interpreted as finding a path on this surface leading to a given image. Our approach is to analyze the properties of this surface, and use its differential or tangential property for visual servoing. The coefficient matrix of the tangent plane of this surface is related to the so-called Interaction Matrix . For this approach, the reduction of the dimension of the image information becomes a key problem. We propose to use the principal component analysis and to represent images with a composition of small number of "" eigenimages "" by using Karhune Loève (K-L) expansion. A normal vector We confirm the feasibility of our basic idea for visual servoing with some experiments using a real robot arm.