Autonomous, or self-driving, cars are emerging as the solution to several problems primarily
caused by humans on roads, such as accidents and traffic congestion. However, those …

Abstract Machine learning and in particular deep learning techniques have demonstrated
the most efficacy in training, learning, analyzing, and modelling large complex structured …

Deep learning has quickly become a necessity for self-driving vehicles on Earth. In contrast,
the self-driving vehicles on Mars, including NASA's latest rover, Perseverance, which is …

This article focuses on learning a model of system dynamics online, while satisfying safety
constraints. Our objective is to avoid offline system identification or hand-specified models …

Planetary rover systems need to perform terrain seg-mentation to identify drivable areas as
well as identify specific types of soil for sample collection. The latest Martian terrain …

This article provides a detailed analysis of the assessment of unmanned ground vehicle
terrain traversability. The analysis is categorized into terrain classification, terrain mapping …

Path planning is an essential technology for lunar rover to achieve safe and efficient
autonomous exploration mission, this paper proposes a learning-based end-to-end path …

Navigating off-road with a fast autonomous vehicle depends on a robust perception system
that differentiates traversable from non-traversable terrain. Typically, this depends on a …

Deep learning has become a powerful tool for Mars exploration. Mars terrain segmentation
is an important Martian vision task, which is the base of rover autonomous planning and safe …

Artificial intelligence (AI), which encompasses machine learning (ML), has become a critical
technology due to its well-established success in a wide array of applications. However, the …