Software verification and validation of safe autonomous cars: A systematic literature review

N Rajabli, F Flammini, R Nardone, V Vittorini - IEEE Access, 2020 - ieeexplore.ieee.org
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 …

[HTML][HTML] A comprehensive survey of unmanned ground vehicle terrain traversability for unstructured environments and sensor technology insights

S Beycimen, D Ignatyev, A Zolotas - Engineering Science and Technology …, 2023 - Elsevier
This article provides a detailed analysis of the assessment of unmanned ground vehicle
terrain traversability. The analysis is categorized into terrain classification, terrain map** …

Ai4mars: A dataset for terrain-aware autonomous driving on mars

RM Swan, D Atha, HA Leopold… - Proceedings of the …, 2021 - openaccess.thecvf.com
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 …

Machine learning techniques for robotic and autonomous inspection of mechanical systems and civil infrastructure

MO Macaulay, M Shafiee - Autonomous Intelligent Systems, 2022 - Springer
Abstract Machine learning and in particular deep learning techniques have demonstrated
the most efficacy in training, learning, analyzing, and modelling large complex structured …

Self-supervised traversability prediction by learning to reconstruct safe terrain

R Schmid, D Atha, F Schöller, S Dey… - 2022 IEEE/RSJ …, 2022 - ieeexplore.ieee.org
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 …

Control barriers in bayesian learning of system dynamics

V Dhiman, MJ Khojasteh… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
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 …

Mars terrain segmentation with less labels

E Goh, J Chen, B Wilson - 2022 IEEE Aerospace Conference …, 2022 - ieeexplore.ieee.org
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 …

[HTML][HTML] Learning-based end-to-end path planning for lunar rovers with safety constraints

X Yu, P Wang, Z Zhang - Sensors, 2021 - mdpi.com
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 …

Robust deep learning LiDAR-based pose estimation for autonomous space landers

Z Chekakta, A Zenati, N Aouf, O Dubois-Matra - Acta Astronautica, 2022 - Elsevier
Accurate relative pose estimation of a spacecraft during space landing operation is critical to
ensure a safe and successful landing. This paper presents a 3D Light Detection and …

Autonomous planetary landing via deep reinforcement learning and transfer learning

G Ciabatti, S Daftry… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
The aim of this work is to develop an application for autonomous landing. We exploit the
properties of Deep Reinforcement Learning and Transfer Learning, in order to tackle the …