Future driver assistance systems will rely on accurate, reliable and continuous knowledge
on the position of other road participants, including pedestrians, bicycles and other vehicles …

Real-time, accurate, and robust localisation is critical for autonomous vehicles (AVs) to
achieve safe, efficient driving, whilst real-time performance is essential for AVs to achieve …

Visual–inertial odometry (VIO) is known to suffer from drifting, especially over long-term runs.
In this article, we present GVINS, a nonlinear optimization-based system that tightly fuses …

For high-level Autonomous Vehicles (AV), localization is highly security and safety critical.
One direct threat to it is GPS spoofing, but fortunately, AV systems today predominantly use …

Unlike loose coupling approaches and the EKF-based approaches in the literature, we
propose an optimization-based visual-inertial SLAM tightly coupled with raw Global …

Lane detection is an important foundation in the development of intelligent vehicles. To
address problems such as low detection accuracy of traditional methods and poor real-time …

Modern vehicles are equipped with a myriad of sensors. Proprioceptive sensors monitor the
vehicle status and operation, whereas exteroceptive ones sense the external environment …

A navigation system which can output drift-free global trajectory estimation with local
consistency holds great potential for autonomous vehicles and mobile devices. We propose …

Despite the remarkable advances in image matching and pose estimation, image-based
localization of a camera in a temporally-varying outdoor environment is still a challenging …

Highly accurate and robust localization ability is of great importance for autonomous
vehicles (AVs) in urban scenarios. Traditional vision-based methods suffer from lost due to …