337 citations · 858 across the 13 of their papers we have counts for
14 papers
Leveraging Stereo-Camera Data for Real-Time Dynamic Obstacle Detection and Tracking
Thomas Eppenberger, Gianluca Cesari, Marcin Dymczyk +2
Dynamic obstacle avoidance is one crucial component for compliant navigation in crowded environments. In this paper we present a system for accurate and reliable detection and trac…
SegMap: Segment-based mapping and localization using data-driven descriptors
Renaud Dubé, Andrei Cramariuc, Daniel Dugas +5
Precisely estimating a robot's pose in a prior, global map is a fundamental capability for mobile robotics, e.g. autonomous driving or exploration in disaster zones. This task, how…
3D Multi-Robot Patrolling with a Two-Level Coordination Strategy
Luigi Freda, Mario Gianni, Fiora Pirri +4
Teams of UGVs patrolling harsh and complex 3D environments can experience interference and spatial conflicts with one another. Neglecting the occurrence of these events crucially h…
AMZ Driverless: The Full Autonomous Racing System
Juraj Kabzan, Miguel de la Iglesia Valls, Victor Reijgwart +19
This paper presents the algorithms and system architecture of an autonomous racecar. The introduced vehicle is powered by a software stack designed for robustness, reliability, and…
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…
Learning 3D Segment Descriptors for Place Recognition
Andrei Cramariuc, Renaud Dubé, Hannes Sommer +2
In the absence of global positioning information, place recognition is a key capability for enabling localization, mapping and navigation in any environment. Most place recognition…
Design of an Autonomous Racecar: Perception, State Estimation and System Integration
Miguel de la Iglesia Valls, Hubertus Franciscus Cornelis Hendrikx, Victor Reijgwart +6
This paper introduces flüela driverless: the first autonomous racecar to win a Formula Student Driverless competition. In this competition, among other challenges, an autonomous ra…
SegMap: 3D Segment Mapping using Data-Driven Descriptors
Renaud Dubé, Andrei Cramariuc, Daniel Dugas +3
When performing localization and mapping, working at the level of structure can be advantageous in terms of robustness to environmental changes and differences in illumination. Thi…
Cone Detection using a Combination of LiDAR and Vision-based Machine Learning
Nico Messikommer, Simon Schaefer, Renaud Dubé +1
The classification and the position estimation of objects become more and more relevant as the field of robotics is expanding in diverse areas of society. In this Bachelor Thesis,…
Autonomous Electric Race Car Design
Niklas Funk, Nikhilesh Alatur, Robin Deuber +12
Autonomous driving and electric vehicles are nowadays very active research and development areas. In this paper we present the conversion of a standard Kyburz eRod into an autonomo…
3D Registration of Aerial and Ground Robots for Disaster Response: An Evaluation of Features, Descriptors, and Transformation Estimation
Abel Gawel, Renaud Dubé, Hartmut Surmann +3
Global registration of heterogeneous ground and aerial mapping data is a challenging task. This is especially difficult in disaster response scenarios when we have no prior informa…
SegMatch: Segment based loop-closure for 3D point clouds
Renaud Dubé, Daniel Dugas, Elena Stumm +3
Loop-closure detection on 3D data is a challenging task that has been commonly approached by adapting image-based solutions. Methods based on local features suffer from ambiguity a…