A robotic arm observes a 3D-printed lunar landscape in Adelaide’s Australian Institute for Machine Learning (AIML) lab.
Sofia McLeod
AI researchers in the South Australian city of Adelaide are hoping to use their own proprietary space technology to revolutionize how spacecraft survey the lunar surface.
Although the first step is to use their AI innovations for lunar surveys, in truth, the technology could be used to survey any planetary surface. That is, if there’s existing data from previously mapped catalogs to take advantage of as a point of reference.
in a paper accepted for publication in the journal Astrodynamics, the authors introduce STELLA (Spacecraft crater-based localization for lunar mapping), a novel AI-powered Crater-Based Navigation pipeline specifically tailored for long-duration lunar mapping missions.
In space, we don’t have GPS, so a spacecraft needs its own way to determine where it is, sofia McLeod, an Australian postdoctoral researcher at Adelaide University’s AI for Space Group and the Andy Thomas Center for Space Resources, tells me via email. There are various positioning methods,such as radio-ranging,but these can have errors of several kilometers,she says.
In contrast, crater-based navigation (CBN) is a vision-based navigation technique that uses images of the Moon’s cratered surface to determine a spacecraft’s position.
And as McLeod and colleagues demonstrate in their paper, STELLA has shown it can achieve much higher accuracy than traditional lunar surveying methods.
How Does It Work?
A camera onboard the spacecraft takes an image of the Moon’s surface; CBN detects craters in that image, matches them to known craters from a pre-existing crater catalog and from these matches determines the spacecraft’s location.