Robot Egomotion from the Deformation of Active Contours

摘要

Traditional sources of information for image-based computer vision algorithms have been points, lines, corners, and recently SIFT features Alternatively, the present work explores the possibility of using tracked contours as informative features, especially in applications not requiring high precision as it is the case of robot navigation. In the past two decades, several approaches have been proposed to solve the robot positioning problem. These can be classified into two general groups Absolute positioning methods estimate the robot position and orientation in the workspace by detecting some landmarks in the robot environment. Two subgroups can be further distinguished depending on whether they use natural landmarks Approaches based on natural landmarks exploit distinctive features already present in the environment. Conversely, artificial landmarks are placed at known locations in the workspace with the sole purpose of enabling robot navigation. This is expensive in terms of both presetting of the environment and sensor resolution. Relative positioning methods, on the other hand, compute the robot position and orientation from an initial configuration, and, consequently, are often referred to as motion estimation methods. A further distinction can also be established here between incremental and nonincremental approaches. Among the former are those based on odometry and inertial sensing, whose main shortcoming is that errors are cumulative. Here we present a motion estimation method that relies on natural landmarks. It is not incremental and, therefore, doesn't suffer from the cumulative error drawback. It uses the images provided by a single camera. It is well known that in the absence of any supplementary information, translations of a monocular vision system can be recovered up to a scale factor. The camera model is assumed to be weak-perspective. The assumed viewing conditions in this model are, first, that the object points are near the projection ray (can be accomplished with a camera having a small field of view), and second, that the depth variation of the viewed object is small compared to its distance to the camera This camera model has been widely used before (