TACTILE TERRAIN PREDICTION FOR AUTONOMOUS AND TELE-OPERATED GROUND VEHICLES

Lidar, Sonar, and Vision-based measurements are often used to preview terrain topology for unmanned ground vehicles. Environmental conditions such as wet or snow-covered roads, shadows, superficial ground coverings, and deceptive surface textures can lead to erroneous measurements. Tactile terrain prediction is both an alternative and a supplement to existing measurement systems. Tactile feedback from an array of low-cost sensors on the moving vehicle is used to generate low wave-number terrain profile predictions. This paper presents tactile terrain prediction results evaluated on four unique courses. Prediction error data are presented up to 25m in front of the vehicle. Results indicate 0.02-0.2m RMS error and 0.18-1.0m peak error at a 10m look-ahead distance. As expected, the prediction errors decrease exponentially as the look-ahead distance decreases. The relatively small prediction errors suggest that the proposed tactile terrain prediction method is a viable low-cost option for use in autonomous and teleoperated ground vehicles.