Load-Bearing Assessment for Safe Locomotion of Quadruped Robots on Collapsing Terrain
Vivian Suzano Medeiros, Giovanni Battista Dessy, Thiago Boaventura, Marcelo Becker, Claudio Semini, Victor Barasuol
AI summary
Problem
Navigating unstable or collapsing surfaces poses significant safety risks for legged robots in search and rescue or planetary exploration. Existing methods rely on expensive specialized sensors, robotic arms, or visual estimation that cannot reliably assess true load-bearing capacity.
Approach
The framework uses standard joint torque and position data to dynamically compute and apply probing forces at candidate footholds, coordinated by a state machine and optimized via Model Predictive Control to balance stability and terrain assessment.
Key results
- Hardware-free load-bearing assessment via joint measurements
- Dynamic probing force calculation through trajectory optimization
- MPC formulation balancing stability and probing constraints
- Experimental validation on collapsing platforms and rocky terrain
Why it matters
Enables safer, hardware-light deployment of commercial quadruped robots in hazardous, unstructured environments like disaster zones or planetary surfaces.
Abstract
Collapsing terrains, often present in search and rescue missions or planetary exploration, pose significant chal- lenges for quadruped robots. This paper introduces a robust locomotion framework for safe navigation over unstable surfaces by integrating terrain probing, load-bearing analysis, motion planning, and control strategies. Unlike traditional methods that rely on specialized sensors or external terrain mapping alone, our approach leverages joint measurements to assess terrain stability without hardware modifications. A Model Predictive Control (MPC) system optimizes robot motion, balancing stability and probing constraints, while a state machine coordinates terrain probing actions, enabling the robot to detect collapsible regions and dynamically adjust its footholds. Experimental results on custom-made collapsing platforms and rocky terrains demon- strate the frameworkâs ability to traverse collapsing terrain while maintaining stability and prioritizing safety.