An Automated Wayfinding Algorithm to Find Rovers' Path on the Lunar South Pole

Abstract

As a part of the upcoming Artemis mission, NASA released a large satellite dataset (latitude, longitude, height, and slope) of the lunar south pole, around the area of the lunar module landing site and rover exploration site near the Shackleton Crater. While designing the rover, it’s important to understand the minimum power the rover needs (the amount of slope it can overcome) to navigate the terrain. Our goal was to process the data, visualize the data in 2-D and 3-D, and develop an algorithm that would automatically map the shortest possible path (or no possible path) between two coordinates according to the lunar terrain and rover parameters.  To accomplish that, we processed a large unorganized dataset into an equally spaced and sequential matrix of latitude, longitude, height, and slope. The matrix was then converted into a go/no-go maze of the terrain and the Breadth First Search (BSF) and A* algorithms were applied to the maze to find the optimal path. The terrain and the optimal path were plotted in 2-D using Matplotlib and interactively displayed in 3D using Plotly.  We developed a Jupyter Notebook web-based app that will allow a user to interactively use the algorithm and visualize the lunar terrain. The results identify the minimum rover slope and various paths depending on higher rover slopes. The algorithm and the rover paths were validated by the NASA SCaN (Satellite Communication and Navigation) team of engineers and the application can be used for design, validation, and training purposes.