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Vibration-based Terrain Analysis for Mobile Robots

Christopher Brooks, Karl Iagnemma, Steven Dubowsky

Year
2006
Citations
75

Abstract

Safe, autonomous mobility in rough terrain is an important requirement for planetary exploration rovers. Knowledge of local terrain properties is critical to ensure a rover’s safety on slopes and uneven surfaces. This paper presents a method to classify terrain based on vibrations induced in the rover structure by wheel-terrain interaction during driving. Vibrations are measured using an accelerometer on the rover structure. The classifier is trained using labeled vibration data during an off-line learning phase. Linear discriminant analysis is used for on-line identification of terrain classes such as sand, gravel, or clay. This approach is experimentally validated on a laboratory testbed.

Keywords

TerrainVibrationTestbedMobile robotAccelerometerComputer scienceRobotRemote sensingArtificial intelligenceGeology

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