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

2026-03-06

AI Summary

This study addresses the failure of legged robots on granular slopes—such as sand dunes—caused by reduced medium shear strength and gravity-induced anisotropic yielding. Through experiments with a hexapod robot on an adjustable-angle granular bed, the authors measure locomotion speed and normal/shear resistive forces to develop a physics-informed robot–terrain interaction model. They innovatively identify anchoring delay and rearward slipping—not sinkage—as the primary causes of performance degradation. Furthermore, they establish the first failure phase diagram that simultaneously incorporates both sinkage and slip-based failure mechanisms, enabling quantitative prediction and boundary delineation of locomotion risk across varying slope angles and terrain strengths. This work provides a theoretical foundation for safe and robust operation of legged robots on deformable inclines.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Model-Based Reasoning
• Natural Language Processing: Safety and Robustness

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• legged robot
• granular slopes
• failure mechanisms
• risk estimation
• locomotion

Innovation

• granular media
• legged locomotion
• failure mechanism
• resistive force model
• risk estimation