A Comparison of Classifier Performance for Vibration-Based Terrain Classification

Abstract

Abstract : The ability to recognize the encountered terrain is an essential part of any terrain-dependent control system designed for mobile robots. Terrains such as sand and gravel make vehicle mobility more difficult and thus reduce vehicle performance. To alleviate this problem the vehicle control system can be tuned for maximum speeds, turning angles, accelerations and other conditions to help adapt to various terrains. Terrain classification can be used to automate the switch from one control mode to another. This paper compares the performance of several classifiers on the problem of vibration-based terrain classification. The purpose of this comparison is to assess the strengths and weaknesses of these techniques in order to better understand the tools available in developing future vibration-based terrain classification algorithms.