The primary focus of this research is on the classification of terrain surfaces to enable automated update of a terrain-dependent control system. This research is motivated by the need for efficient and safe control of autonomous ground vehicles (AGVs) on outdoor terrains such as grass, gravel, sand, asphalt and ice. Terrain classification algorithms have been developed using both vision sensors and proprioceptive sensing such as direct vibration measurements and slip estimates. The research has also developed a methodology for filtering misclassifications so that the control system does not change due to these misclassifications. Ongoing research also includes the application of terrain classification to electric powered wheelchairs (EPWs) as part of the development of a terrain-dependent EPW control system.