This article presents a challenging multi-agent seasonal dataset collected by a fleet of Ford
autonomous vehicles (AVs) at different days and times during 2017–2018. The vehicles …

Image retrieval-based cross-view localization methods often lead to very coarse camera
pose estimation, due to the limited sampling density of the database satellite images. In this …

Existing spatial localization techniques for au-tonomous vehicles mostly use a pre-built 3D-
HD map, often constructed using a survey-grade 3D mapping vehicle, which is not only …

This paper proposes a novel method for geo-tracking, ie continuous metric self-localization
in outdoor environments by registering a vehicle's sensor information with aerial imagery of …

We present a novel framework for global localization and guided relocalization of a vehicle
in an unstructured environment. Compared to existing methods, our pipeline does not rely …

6-DoF visual localization systems utilize principled approaches rooted in 3D geometry to
perform accurate camera pose estimation of images to a map. Current techniques use …

Cross-modal vehicle localization is an important task for automated driving systems. This
research proposes a novel approach based on LiDAR point clouds and OpenStreetMaps …

The use of robotic systems in organic farming has taken on a leading role in recent years;
the Sureveg CORE Organic Cofund ERA-Net project seeks to evaluate the benefits of strip …

This paper proposes a novel framework for real-time localization and egomotion tracking of
a vehicle in a reference map. The core idea is to map the semantic objects observed by the …

Localization in aerial imagery-based maps offers many advantages, such as global
consistency, geo-referenced maps, and the availability of publicly accessible data. However …