Related papers: Failure Mechanisms and Risk Estimation for Legged Robot Locomotion on Granular Slopes

Failure Mechanisms and Risk Estimation for Legged Robot Locomotion on Granular Slopes

URL: http://arxiv.org/abs/2603.06928v1
Date: Fri, 06 Mar 2026 22:58:45 GMT
Title: Failure Mechanisms and Risk Estimation for Legged Robot Locomotion on Granular Slopes
Abstract summary: Locomotion on granular slopes is a challenge for legged robots due to reduced shear strength and gravity-induced anisotropic yielding of granular media.<n>Using a hexapedal robot on a tiltable granular bed, we measure locomotion speed together with slope-dependent normal and shear granular resistive forces.<n>We develop a simple robot-terrain interaction model that predicts anchoring timing, step length, and resulting robot speed, as functions of terrain strength and slope angle.
Score: 1.6267479602370543
License: http://creativecommons.org/licenses/by-sa/4.0/
Abstract: Locomotion on granular slopes such as sand dunes remains a fundamental challenge for legged robots due to reduced shear strength and gravity-induced anisotropic yielding of granular media. Using a hexapedal robot on a tiltable granular bed, we systematically measure locomotion speed together with slope-dependent normal and shear granular resistive forces. While normal penetration resistance remains nearly unchanged with inclination, shear resistance decreases substantially as slope angle increases. Guided by these measurements, we develop a simple robot-terrain interaction model that predicts anchoring timing, step length, and resulting robot speed, as functions of terrain strength and slope angle. The model reveals that slope-induced performance loss is primarily governed by delayed anchoring and increased backward slip rather than excessive sinkage. By extending the model to generalized terrain conditions, we construct failure phase diagrams that identify sinkage- and slippage-induced failure regimes, enabling quantitative risk estimation for locomotion on granular slopes. This physics-informed framework provides predictive insight into terrain-dependent failure mechanisms and offers guidance for safer and more robust robot operation on deformable inclines.

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