3 accepted papers
We present a novel machine learning framework and synthetic dataset for performing absolute localization on planetary surfaces where satellite navigation systems are unavailable. Current approaches involve manual surface-to-satellite image matching by human rover operators, limiting the rate of plan
Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on optimal motion planning has employed two main strategies to define a safe bound on an obstacle's space: using a polyhedron or a nonlinear differe
We present a neural network approach and publicly available dataset for developing and benchmarking algorithms for localization on the Moon. Accurate localization is essential for navigation, path planning, and science objectives. On Earth, localization can be achieved using a satellite navigation s…