In this article, we present how it is possible to recover physical parameters of objects such as reflectivity, emissivity and thermal inertia from the analysis of infrared images in outdoor scenes. Our approach is based on the extensive use of the physical laws that are at the origin of the formation of images. First, we derive a physical model that describes how surface patches of ob-jects appear in infrared images. Second, in order to calculate the physical properties of objects, we inverse this model by using a least square fitting method. Because of the non-linearity of the model, we show that it is diffi-cult to obtain accurate results about the physical properties. To overcome this limitation, we demonstrate that, under several assumptions, there exist some physical invariants that are more reliable than physical parameters. 1

The authors are prototyping a legged vehicle, the Ambler, for an exploratory mission on another planet, conceivably Mars, where it is to traverse uncharted areas and collect material samples. They describe how the rover can construct from range imagery a geometric terrain representation, i.e., elevation map that includes uncertainty, unknown areas, and local features. First, they present an algorithm for constructing an elevation map from a single range image. By virtue of working in spherical-polar space, the algorithm is independent of the desired map resolution and the orientation of the sensor, unlike algorithms that work in Cartesian space. Secondly, the authors present a two-stage matching technique (feature matching followed by iconic matching) that identifies the transformation T corresponding to the vehicle displacement between two viewing positions. Thirdly, to support legged locomotion over rough terrain, they describe methods for evaluating regions of the constructed elevation maps as footholds.>