Slip estimation methods for proprioceptive terrain classification using tracked mobile robots

Abstract

Recent work has shown that proprioceptive measurements such as terrain slip can be used for terrain classification. This paper investigates the suitability of four simple slip estimation methods for differentiating between indoor and outdoor terrain surfaces, namely: rocks, grass, rubber and carpet. These slip estimates are calculated using experimental odometric data collected from a tracked autonomous ground vehicle and comprise of two instantaneous estimators and a temporal windowing approach. Results show that only the temporal windowing approach shows significant differences across the terrains investigated, indicating that instantaneous measurements are unsuited to terrain classification.