Martian Terrain

Research on Martian terrain focuses on improving autonomous navigation and scientific understanding of the planet's surface. Current efforts utilize deep learning models, including convolutional neural networks and encoder-decoder architectures, to perform tasks such as semantic segmentation of surface features (e.g., identifying "brain coral" terrain), object detection for hazard avoidance during landing, and even predicting climate variables like relative humidity. These advancements are crucial for optimizing rover operations, selecting optimal landing sites, and expanding our knowledge of Martian geology and past habitability.