Terramechanics-Based Mobility Failure Compensation and Soil Manipulation
Catherine Pavlov, Arno Rogg, Aaron M. Johnson
AI summary
Problem
Planetary rovers currently rely on ad-hoc, trial-and-error methods to handle terrain manipulation and mobility system failures, risking mission success on long-duration missions.
Approach
The authors use a terramechanics wheel-soil interaction model within an optimization framework to automatically generate open- and closed-loop driving strategies for off-nominal rover operations.
Key results
- Full-scale rover digs trenches up to 10.6 cm deep while driving
- Doubled wheel slip observed on moderate slopes with a damaged drive motor
- Optimization framework automatically generates driving strategies without manual tuning
- Lab validation confirms maintained mobility during soil manipulation and recovery from actuator failures
Why it matters
Provides a scalable, hardware-free solution for extending rover mission lifespans and scientific return in degraded or unstructured environments.
Abstract
In this paper, we enable new mobility and manipulation modes for wheeled planetary exploration rovers through the use of terramechanics modeling and field experiments. Useful modes of wheel-based soil manipulation and examples of rovers driving with degraded mobility systems are first demonstrated in lunar and Martian analog environments. We show a full-scale rover use its wheels to dig trenches up to 10.6 cm deep, dig holes to estimate soil characteristics, and modify terrain to make it accessible to a smaller robot. We also measure the impact of actuator failure on a rover in lunar simulant. Here, we show the slip doubled on moderate slopes for a damaged drive motor, which would exceed the rover’s operational limits for slip, motivating the need for driving strategies that mitigate mobility loss. We then develop an optimization framework which uses a recently developed terramechanics model to automatically generate both open and closed-loop driving strategies for planetary rovers performing terrain manipulation or operating in a degraded state with no need for hand tuning of behaviors. Finally, we demonstrate the generated driving strategies for soil manipulation and mobility compensation on a rover in a controlled lab setting, where we show that 1) mobility is maintained while manipulating soil; and 2) mobility is regained while experiencing failure of steer and drive actuators.