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Considering measurement uncertainty in dynamic object tracking for autonomous driving applications

Bedeutung der Messunsicherheit beim Tracking dynamischer Objekte im Bereich des autonomen Fahrens
Benjamin Naujoks

Benjamin Naujoks studied technomathematics (scientific computing & optimization) at the Technical University of Dresden. Since 2015 he has been researching autonomous driving at the University of the Bundeswehr Munich. His research interests include probabilistic filter algorithmic, object-detection, especially in LiDAR point-clouds, parallelization with CUDA and machine-learning algorithms.

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, Torsten Engler

Torsten Engler studied electrical engineering and information technologies at the Technical University Munich. He is researching in the context of autonomous driving at the University of the Bundeswehr Munich since 2014. His research focus lays on camera assisted driving in non urban environments including vision-based obstacle avoidance and 3D reconstruction of the environment.

, Martin Michaelis

Martin Michaelis studied mathematics at the University of Bonn. Afterwards, he worked two years as a research assistant at the Fraunhofer institute FKIE in Wachtberg. Since 2016, he is with the University of the Bundeswehr Munich. His main research interests are multi-object tracking, multi-sensor fusion and extended target tracking.

, Thorsten Luettel

Thorsten Luettel studied electrical engineering (mechatronics) at the Leibniz Universität Hannover. Since 2006 he has been researching autonomous driving at the University of the Bundeswehr Munich. Recently, he has also led ‘Team MuCAR’ during successful international competitions. His research interests include sensor data fusion and system integration.

and Hans-Joachim Wuensche

Hans-Joachim Wuensche got his PhD from University of the Bundeswehr Munich in 1987 with Ernst D. Dickmanns, where he co-developed the 4D-approach to computer vision. After many years in management, he returned to the same University to lead the Institute for Autonomous Systems Technology in 2004. His research interests include autonomous robots, especially on- and off-road vehicles exploring and navigating unknown terrain.

From the journal tm - Technisches Messen

Abstract

Measurement uncertainty plays an important role in every real-world perception task. This paper describes the influence of measurement uncertainty in state estimation, which is the main part of Dynamic Object Tracking. Its base is the probabilistic Bayesian Filtering approach. Practical examples and tools for choosing the correct filter implementation including measurement models and their conversion, for different kinds of sensors are presented.

Zusammenfassung

Die korrekte Modellierung der Messunsicherheit ist eine große Herausforderung für die Wahrnehmung im Bereich Autonomes Fahren unter realen Bedingungen. In diesem Artikel beschreiben wir den Einfluss der Messunsicherheit sowie deren Behandlung in der Zustandsschätzung, welche die Grundlage für das Tracking dynamischer Objekte ist. Die Basis hierfür ist die probabilistische Bayessche Filterung. Weiterhin werden praktische Beispiele und Techniken zur korrekten Filterimplementierung einschließlich verschiedener Messmodelle sowie deren Konvertierung betrachtet.

About the authors

Benjamin Naujoks

Benjamin Naujoks studied technomathematics (scientific computing & optimization) at the Technical University of Dresden. Since 2015 he has been researching autonomous driving at the University of the Bundeswehr Munich. His research interests include probabilistic filter algorithmic, object-detection, especially in LiDAR point-clouds, parallelization with CUDA and machine-learning algorithms.

Torsten Engler

Torsten Engler studied electrical engineering and information technologies at the Technical University Munich. He is researching in the context of autonomous driving at the University of the Bundeswehr Munich since 2014. His research focus lays on camera assisted driving in non urban environments including vision-based obstacle avoidance and 3D reconstruction of the environment.

Martin Michaelis

Martin Michaelis studied mathematics at the University of Bonn. Afterwards, he worked two years as a research assistant at the Fraunhofer institute FKIE in Wachtberg. Since 2016, he is with the University of the Bundeswehr Munich. His main research interests are multi-object tracking, multi-sensor fusion and extended target tracking.

Thorsten Luettel

Thorsten Luettel studied electrical engineering (mechatronics) at the Leibniz Universität Hannover. Since 2006 he has been researching autonomous driving at the University of the Bundeswehr Munich. Recently, he has also led ‘Team MuCAR’ during successful international competitions. His research interests include sensor data fusion and system integration.

Hans-Joachim Wuensche

Hans-Joachim Wuensche got his PhD from University of the Bundeswehr Munich in 1987 with Ernst D. Dickmanns, where he co-developed the 4D-approach to computer vision. After many years in management, he returned to the same University to lead the Institute for Autonomous Systems Technology in 2004. His research interests include autonomous robots, especially on- and off-road vehicles exploring and navigating unknown terrain.

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Received: 2018-03-15
Accepted: 2018-10-30
Published Online: 2018-11-21
Published in Print: 2018-12-19

© 2018 Walter de Gruyter GmbH, Berlin/Boston

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