Urban Navigation

LUCOOP: Leibniz University Cooperative Perception and Urban Navigation Dataset

There is currently a lack of comprehensive, real-world, multi-vehicle datasets fostering research on cooperative applications such as object detection, urban navigation, or multi-agent SLAM. In this paper, we aim to fill this gap by introducing the novel LUCOOP dataset, which provides time-synchronized multi-modal data collected by three interacting measurement vehicles.

Jul 27, 2023

Advances in deterministic approaches for bounding uncertainty and integrity monitoring of autonomous navigation
Advances in deterministic approaches for bounding uncertainty and integrity monitoring of autonomous navigation

In this contribution, we aim to demonstrate the feasibility of applying the alternative integrity approach to autonomous navigation in terms of several key aspects, i.e., the handling of GNSS multipath effect in the urban environment, fault detection and exclusion, and further consideration of applying weighting models.

Sep 20, 2022

Towards integrity for GNSS-based urban navigation - challenges and lessons learned

For safety critical applications like autonomous driving, high trust in the reported navigation solution is mandatory. This trust can be expressed by the navigation performance parameters, especially integrity. Multipath errors are the most challenging error source in GNSS since only partial correction is possible. In order to ensure high integrity of GNSS-based urban navigation, signal propagation mechanisms and the potential error sources induced by the complex measurement environment should be sufficiently understood.

Jun 5, 2022

Improved observation interval bounding for multi-GNSS integrity monitoring in urban navigation

Sep 20, 2021