Planetary Localization in GPS-Deprived Environments with Open-Source Software and Commercial-Off–the-Shelf Components

Autonomous unmanned vehicles can perform detailed surveys of planetary surfaces but it is imperative to establish a method for global localization to effectively explore these areas. The absence of GPS in extraplanetary environments prevents surface vehicles from knowing their exact location, which raises the need for an alternative positioning system. Traditional methods, such as visual odometry cross-referenced with digital elevation maps, are limited by their dependence on human input and pre-existing space infrastructure. This paper outlines and characterizes a global position determination algorithm intended for planetary surface vehicles in GPS-denied environments without any prior knowledge. The localization algorithm receives images of the stars from a visible camera and tilt measurements from an inclinometer, derives star locations and a gravity vector, and combines these signals to generate an onboard position determinant. This paper contributes (i) the first open-source planetary global localization algorithm based on stars, (ii) a sensor suite design derived of solely commercial-off-the-shelf (COTS) components, and (iii) an unprecedented physical experiment and characterization from this algorithm on Earth’s surface. The resulting position determinant is on average 100km from the testing location, consistent across various time and surface inclines. This result is compared to theoretical performance, state-of-the-art sensor performance, and other global localization methods. This achieved determinant error offers a starting point toward localization improvement with more capable sensors and the incorporation of multiple historical determinants for state estimation.