Towards Proprioceptive Terrain Mapping with Quadruped Robots for Exploration in Planetary Permanently Shadowed Regions

TL;DR

This paper presents a proprioceptive terrain mapping framework for quadruped robots to explore lunar shadowed regions, enabling in-situ terrain interaction assessment beyond traditional exteroceptive sensors.

Contribution

It introduces a novel proprioceptive mapping method that estimates terrain interaction metrics from internal sensors during robot locomotion in lunar-like environments.

Findings

Consistent terrain mapping performance in lunar gravity simulations.

Effective estimation of elevation, slippage, and stability metrics.

Framework suitable for challenging extraterrestrial terrains.

Abstract

Permanently Shadowed Regions (PSRs) near the lunar poles are of interest for future exploration due to their potential to contain water ice and preserve geological records. Their complex, uneven terrain favors the use of legged robots, which can traverse challenging surfaces while collecting in-situ data, and have proven effective in Earth analogs, including dark caves, when equipped with onboard lighting. While exteroceptive sensors like cameras and lidars can capture terrain geometry and even semantic information, they cannot quantify its physical interaction with the robot, a capability provided by proprioceptive sensing. We propose a terrain mapping framework for quadruped robots, which estimates elevation, foot slippage, energy cost, and stability margins from internal sensing during locomotion. These metrics are incrementally integrated into a multi-layer 2.5D gridmap that reflects terrain interaction from the robot's perspective. The system is evaluated in a simulator that mimics a lunar environment, using the 21 kg quadruped robot Aliengo, showing consistent mapping performance under lunar gravity and terrain conditions.