An acute problem of determining the motion from two perspective views has to be solved in order to make mobile robot navigation work. Structure from motion is needed in many applications including monitoring dynamic industrial processes and image processing. It is known [14,15] that existing techniques for motion estimation perform poorly on real images, when the image-point feature are noisy. This paper describes new, robust techniques to recover structure and movement from noisy images. Closed-form solutions are derived for the case of general three-dimensional motion. These solutions are used as initial estimate for another technique, called reconstruction and reprojection. We also present a solution for the case of planar motion, which is the case of a mobile robot moving over a flat surface. These techniques have been tested on synthetic as well as real images and the test results are described and compared with an improved version of LONGUET-HIGGINS [18] technique.