Effect of Gait Design on Proprioceptive Sensing of Terrain Properties in a Quadrupedal Robot

2025-09-26

AI Summary

This study investigates how gait design influences proprioceptive in-situ identification of mechanical properties—such as strength and brittle failure—of soft, deformable terrains by quadrupedal robots. Method: We propose and experimentally validate a perception-oriented slow crawling gait, “Crawl N’ Sense,” benchmarked against a locomotion-oriented trot-walk gait across rigid ground, loose sand, and simulated crust-covered terrain. Contribution/Results: Both gaits enable discrimination among substrates with differing resistive properties; however, “Crawl N’ Sense” significantly reduces measurement variance and achieves higher accuracy in detecting crust rupture events. This work establishes the first empirical principle for “perception-in-motion” gait design—demonstrating that deliberate, low-speed, high-contact-duration locomotion enhances proprioceptive fidelity. It delivers a deployable gait paradigm and experimental validation for in-situ terrain mechanical assessment via proprioception, with direct relevance to planetary exploration and other autonomous field robotics applications.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• 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
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

In-situ robotic exploration is an important tool for advancing knowledge of geological processes that describe the Earth and other Planetary bodies. To inform and enhance operations for these roving laboratories, it is imperative to understand the terramechanical properties of their environments, especially for traversing on loose, deformable substrates. Recent research suggested that legged robots with direct-drive and low-gear ratio actuators can sensitively detect external forces, and therefore possess the potential to measure terrain properties with their legs during locomotion, providing unprecedented sampling speed and density while accessing terrains previously too risky to sample. This paper explores these ideas by investigating the impact of gait on proprioceptive terrain sensing accuracy, particularly comparing a sensing-oriented gait, Crawl N' Sense, with a locomotion-oriented gait, Trot-Walk. Each gait's ability to measure the strength and texture of deformable substrate is quantified as the robot locomotes over a laboratory transect consisting of a rigid surface, loose sand, and loose sand with synthetic surface crusts. Our results suggest that with both the sensing-oriented crawling gait and locomotion-oriented trot gait, the robot can measure a consistent difference in the strength (in terms of penetration resistance) between the low- and high-resistance substrates; however, the locomotion-oriented trot gait contains larger magnitude and variance in measurements. Furthermore, the slower crawl gait can detect brittle ruptures of the surface crusts with significantly higher accuracy than the faster trot gait. Our results offer new insights that inform legged robot "sensing during locomotion" gait design and planning for scouting the terrain and producing scientific measurements on other worlds to advance our understanding of their geology and formation.

Problem

• Investigating how gait design affects terrain sensing accuracy in legged robots
• Comparing locomotion-oriented and sensing-oriented gaits for terrain property measurement
• Evaluating gait performance on deformable substrates with varying strength and texture

Innovation

• Sensing-oriented gait for terrain property detection
• Proprioceptive sensing with direct-drive actuators
• Comparing crawling and trotting gaits' sensing accuracy