ShadowNav: Autonomous Global Localization for Lunar Navigation in Darkness

TL;DR

ShadowNav is an autonomous lunar localization system that uses crater landmarks and particle filtering to enable rovers to navigate in darkness without human intervention, demonstrated in simulation and field tests.

Contribution

It introduces a novel crater-based localization method for lunar rovers that operates autonomously in darkness, reducing reliance on ground control and manual corrections.

Findings

Effective crater landmark association in simulation and field tests

Successful autonomous localization in lunar-like conditions

Robust performance in darkness and low-light environments

Abstract

The ability to determine the pose of a rover in an inertial frame autonomously is a crucial capability necessary for the next generation of surface rover missions on other planetary bodies. Currently, most on-going rover missions utilize ground-in-the-loop interventions to manually correct for drift in the pose estimate and this human supervision bottlenecks the distance over which rovers can operate autonomously and carry out scientific measurements. In this paper, we present ShadowNav, an autonomous approach for global localization on the Moon with an emphasis on driving in darkness and at nighttime. Our approach uses the leading edge of Lunar craters as landmarks and a particle filtering approach is used to associate detected craters with known ones on an offboard map. We discuss the key design decisions in developing the ShadowNav framework for use with a Lunar rover concept equipped with a stereo camera and an external illumination source. Finally, we demonstrate the efficacy of our proposed approach in both a Lunar simulation environment and on data collected during a field test at Cinder Lakes, Arizona.