Vision-based terrain characterization and traversability assessment

This article presents novel techniques for real-time terrain characterization and assessment of terrain traversability for a field mobile robot using a vision system and artificial neural networks. The key terrain traversability characteristics are identified as roughness, slope, discontinuity, and hardness. These characteristics are extracted from imagery data obtained from cameras mounted on the robot and are represented in a fuzzy logic framework using perceptual, linguistic fuzzy sets. The approach adopted is highly robust and tolerant to imprecision and uncertainty inherent in sensing and perception of natural environments. The four traversability characteristics are combined to form a single Fuzzy Traversability Index, which quantifies the ease-of-traversal of the terrain by the mobile robot. Experimental results are presented to demonstrate the capability of the proposed approach for classification of different terrain segments based on their traversability. (C) 2001 John Wiley & Sons, Inc.