Abstract: This paper describes a vision and 3D laser based registration approach which utilizes visual features to identify correspondences. Visual features are obtained from the images of a standard color camera and the depth of these features is determined by interpolating between the scanning points of a 3D laser range scanner, taking into consideration the visual information in the neighbourhood of the respective visual feature. The 3D laser scanner is also used to determine a position covariance estimate of the visual feature. To exploit these covariance estimates, an ICP algorithm based on the Mahalanobis distance is applied. Initial experimental results are presented in a real world indoor laboratory environment.