Terrain Traversability Prediction by Imaging Thermal Transients

Abstract

The inability of current robotic perception techniques to adequately detect non-geometric terrain hazards is a primary cause of failure for robots operating in natural terrain on Mars, the Moon, and Earth. Classical approaches detect surface appearance but do not measure the underlying mechanical properties that determine wheel-terrain interaction. Diurnal temperature variations of a granular material, however, are strongly correlated with both its surface appearance and subsurface geophysical properties. This paper presents a technique for determining relative differences in looseness and traversability of granular terrain through analysis of thermal imagery. Terrain compaction and traversability are predicted by estimating a material’s thermal inertia from observations of thermal transients. Results from a set of experiments in sandy terrain demonstrate the ability of this approach to differentiate between safe, compact and hazardous, loose terrain.