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Angewandte Technisch-Kognitive Systeme/en: Unterschied zwischen den Versionen

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         <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]
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         <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li>
 
         <li>[https://www.aifb.kit.edu/web/Daniel_Bogdoll Anomaly Detection for Autonomous Driving]</li>
 
         <li>[https://www.aifb.kit.edu/web/Daniel_Bogdoll Anomaly Detection for Autonomous Driving]</li>
 
         <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Robust, interpretable and energy-efficient deep learning for camera-based perception]</li>
 
         <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Robust, interpretable and energy-efficient deep learning for camera-based perception]</li>
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        <li>[https://www.aifb.kit.edu/web/Tobias_Fleck Sensorfusion for connected autonomous driving]</li>
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        <li>[https://www.aifb.kit.edu/web/Tobias_Fleck Intelligent roadside infrastructure for connected autonomous driving]</li>
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        <li>[https://aifb.kit.edu/web/Stefan_Orf Recognition of Sensor Data Discrepancies in Autonomous Vehicles and Smart Infrastructure]</li>
 
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         <li>[https://aifb.kit.edu/web/Albert_Schotschneider Misbehavior Detection and Optimization of Driving Components for Robustness Improvement] </li>
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         <li>[https://aifb.kit.edu/web/Albert_Schotschneider Misbehavior Detection and Optimization of Driving Components for Robustness Improvement]</li>
 
         <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Adversarial Attacks on Deep Learning Models]</li>
 
         <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Adversarial Attacks on Deep Learning Models]</li>
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        <li>[https://aifb.kit.edu/web/Stefan_Orf Condition Monitoring for Robust and Safe Autonomous Systems]</li>
 
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         <li>[https://www.aifb.kit.edu/web/Marc_Zofka Vehicle-to-everything (V2X) for Distributed Simulations on Proving Grounds and Test Areas for Autonomous Driving]</li>
 
         <li>[https://www.aifb.kit.edu/web/Marc_Zofka Vehicle-to-everything (V2X) for Distributed Simulations on Proving Grounds and Test Areas for Autonomous Driving]</li>
 
         <li>[https://aifb.kit.edu/web/Martin_Gontscharow Interactive Machine Learning for Remote Assisted Autonomous Vehicles]</li>
 
         <li>[https://aifb.kit.edu/web/Martin_Gontscharow Interactive Machine Learning for Remote Assisted Autonomous Vehicles]</li>
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        <li>[https://aifb.kit.edu/web/Stefan_Orf Remote Operation in Autonomous Driving]</li>
 
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Version vom 21. Oktober 2022, 08:19 Uhr


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Description

The research focuses on technologies of applied machine intelligence. Based on fundamental research new systems such as autonomous service robots, autonomous vehicles or assistance systems with cognitive capabilities are to be realized. The use of these so-called technical-cognitive systems takes place primarily in the context of highly automated, efficient and intermodal mobility; connected, automated production and logistics as well as the interactive support of the user in everyday situations.

Perception, situation assessment as well as decision making are the primarily addressed basics of machine intelligence. Methods for machine learning and probabilistic inference are thereby researched and applied for all components. The holistic use of neural methods in the areas of adaptive perception and behavioral decision making is being accounted for in the long term with the newly formed research focus of neurorobotics. Procedures for system evaluation and validation form an additional focus in the context of applied research. Autonomous vehicles like CoCar and CoCar-Zero, mobile robots such as the assistant robot Hollie, the walking robot Lauron or the inspection robot Cairo thereby form valuable integration and evaluation platforms for applied research. They are developed in close cooperation with the FZI and used for joint research and teaching.



News
2024-03-12: Autonomous driving with Federal Minister for Digital and Transport Volker Wissing on Campus North
2023-10-05: Autonomous driving with Federal Minister for Digital and Transport Volker Wissing on Campus North
2023-10-05: CoCar NextGen at IEEE ITSC 2023
2023-10-05: CoCar NextGen at IEEE ITSC 2023
2020-09-21: Best Dissertation Award - IEEE ITS Society
2018-11-15: Audi Autonomous Driving Cup 2018: Team AlpaKa wins the title
2018-11-05: Best Paper Award - IEEE International Conference on Intelligent Transportation Systems (ITSC)
2018-06-28: Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)
2018-06-28: Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)


Open Theses and Hiwi-Jobs

Research Area

Research Topics

Perception

Prediction

Maps

Planning

Safety and Security

Vehicle-to-Everything (V2X/Car2X)

Simulation

End-to-end learning

Mixed Reality

Reinforcement Learning

Other Topics in Autonomous Driving



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Intelligent Systems and Production Engineering



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Active Projects
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SPP 1835: Kooperativ interagierende Automobile
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SofDCar
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Testfeld Autonomes Fahren
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