Vibration-based terrain classification using surface profile input frequency responses

Terrain variations can greatly influence autonomous ground vehicle (AGV) performance. However, if the terrain is properly identified, the AGV control systems can be adjusted to better suit the terrain. Current terrain classification techniques are largely based on vision and terrain dependent vehicle reactions. But at this time both methods have limitations. Visual methods can easily be fooled by fallen leaves or other superficial ground coverings, whereas response-based methods yield poor results when the AGV speed is significantly different from the training speeds. In addition, current response-based methods are not capable of identifying the multiple terrains that a vehicle may simultaneously traverse, e.g., when one subset of wheels is on-road and one is off-road. This paper proposes a response-based method called terrain input classification to solve the issue of speed dependency and multiple terrain traversal. This method is dependent upon knowing the vibration transfer function of the AGV. The method has been verified through terrain-based simulation results and is ready for experimental testing.