A monocular vision sensor on a mobile robot for finding and tracking a feature point in 3D space while it moves along a route is described. Visual feedback is used to fix the feature point, called the fixation point, at the image center. The precise information of the camera angular velocity is used for estimating 3D structure around the fixation point to build a local map. Mathematical equations for linear and circular robot motions are given. Experimental results show the validity of this method.>

This paper describes a technique for measuring the movement of edge-lines in a sequence of images by maintalning an image plane model. Edge-lines are expressed as a set of parameter vectors representing the center-point, orientation and length of a segment. Each parameter vector is composed of an estimate, a temporal derivative, and their covariance matrix. Line segment parameters in the flow model are updated using a Kalman filter. The eorrespondance of observed edge-lines segments to segments predicted from the flow model is determined by a linear complexity algorithm using distance normalized by covariance. The existence of segments in the flow model is controlled using a confidence factor. This technique is in everyday use as part of a larger system for building 3-D scene descriptions using a camera mounted on a robot arm. A near video-rate hardware implementation is currently under development