RobustSense's key goal is to deliver a robust and reliable environment sensing and situation prediction for ADAS and automated driving. Major improvements of the hardware for environment sensing allow for an increase of robustness during harsh weather conditions.

By incorporating probabilistic information throughout all software modules, the overall sensor platform will provide a higher reliability for already existing sensors combinations as well as novel ones. Sensor uncertainties and conflicting information will be reflected in the environment model and will thus affect the results of situation understanding and prediction modules as well as behaviour and trajectory estimation. For each module, closely connected assessment nodes are developed to provide an estimation of the current performance of the sensor platform. A common system assessment node combines the performance assessment and will provide the available performance level of the full system. In cases of decreasing performance due to weather conditions or sensor malfunctions, the sensor platform is then able to decide for functional degradation.

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Dipl.-Math. techn. Florian Kuhnt

Research Scientist



Florian Kuhnt studierte bis 2012 Technomathematik am Karlsruher Institut für Technologie (KIT). Seine Schwerpunkte liegen in den Gebieten Kognitive Systeme und Robotik.

Seine Diplomarbeit mit dem Titel „Probabilistische Kollisionsprädiktion für Segway-Transporter“ führte er in der Abteilung Technisch Kognitive Systeme (TKS) am Forschungszentrum Informatik (FZI) durch.

Seit Juni 2012 ist er wissenschaftlicher Mitarbeiter in der Abteilung TKS. Er ist im Bereich der Hinderniserkennung und -bewertung, sowie der Situationsanalyse und -interpretation tätig.


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