<title>Accuracy of scene reconstruction with an active stereo vision system using motorized zoom lenses</title>

Abstract

In this paper the active stereo vision system KASTOR of the IPR and its calibration technique are described. KASTOR is designed to serve as a flexible sensing device mounted on a mobile robot platform. It is used for collision avoidance, navigation based on natural landmarks, and object recognition. KASTOR has eight motorized optical and mechanical degrees of freedom. The article describes the design of KASTOR as well as the real-time vision system it is connected to. A new camera calibration technique for an active vision system is presented. The DLT-matrices (direct linear transformation) are computed directly by the observation of a reference object in a scene. A solution to the problem that the accuracy in the detection of reference points in the images is very low is presented. With the presented method reference points can be located with sub-pixel accuracy. As KASTOR alters any of its degrees of freedom, the calibration has to be updated. However, it is not possible to track a reference object when the head is mounted on a mobile robot. The new solution is to compute all possible DLT-matrices in advance and to store them in the memory. During autonomous operation the right matrices are selected according to the head-configuration. Experimental results prove that the accuracy of the new calibration technique is absolutely sufficient to use KASTOR as a sensor for the navigation of a mobile robot. This is shown in an example where the task is to navigate the mobile robot through a narrow door only based on active stereo vision sensing.