Mobile robot terrain perception is needed to provide local terrain data to assess route trafficability. Important terrain features include positive obstacles (e.g., rocks, walls and posts), negative obstacles (e.g., down-steps, gaps and holes), step slopes (lateral and longitudinal), and broken, rough or porous obstacles (e.g., brush and rubble). Terrain perception is needed to locate these terrain features and assess their geometric properties. Stereo vision (stereoscopy) is a widely-used technique for mobile robot terrain perception. Stereo vision is effective for locating positive obstacles. It has not proven effective at locating and assessing negative features, slope in regions with relatively uniform in appearance, or highly textured features. This paper explores an approach to enhance and complement stereo vision terrain perception by using simple stereo lighting (photometric stereo). Shadows created by vertical- offset lighting are an effective cue to locate negative terrain features. Horizontal-offset illumination enhances cue features in the scene for stereo vision processing. Stereo illumination creates depth cues that can not be exploited by traditional horizontal-offset stereo vision systems, but can be exploited by trinocular or vertically- offset stereo cameras. Multiple light sources and cameras enable shape-from-shading (photoclinometry) methods to overcome traditional limitations to generating 3D range and slope maps for natural terrain. Issues in applying these methods for broken, rough and porous obstacles are identified, but not examined in detail.