2 citations · 2 across the 3 of their papers we have counts for
8 papers
MOZARD: Multi-Modal Localization for Autonomous Vehicles in Urban Outdoor Environments
Lukas Schaupp, Patrick Pfreundschuh, Mathias Buerki +3
Visually poor scenarios are one of the main sources of failure in visual localization systems in outdoor environments. To address this challenge, we present MOZARD, a multi-modal l…
Accurate Mapping and Planning for Autonomous Racing
Leiv Andresen, Adrian Brandemuehl, Alex Hönger +11
This paper presents the perception, mapping, and planning pipeline implemented on an autonomous race car. It was developed by the 2019 AMZ driverless team for the Formula Student G…
Deep Unsupervised Common Representation Learning for LiDAR and Camera Data using Double Siamese Networks
Andreas Bühler, Niclas Vödisch, Mathias Bürki +1
Domain gaps of sensor modalities pose a challenge for the design of autonomous robots. Taking a step towards closing this gap, we propose two unsupervised training frameworks for f…
OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios
Lukas Schaupp, Mathias Bürki, Renaud Dubé +2
We introduce a novel method for oriented place recognition with 3D LiDAR scans. A Convolutional Neural Network is trained to extract compact descriptors from single 3D LiDAR scans.…
VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments
Mathias Bürki, Lukas Schaupp, Marcin Dymczyk +4
Changes in appearance is one of the main sources of failure in visual localization systems in outdoor environments. To address this challenge, we present VIZARD, a visual localizat…
Redundant Perception and State Estimation for Reliable Autonomous Racing
Nikhil Bharadwaj Gosala, Andreas Bühler, Manish Prajapat +9
In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences. To limit the impact of such failures, this paper present…