Angewandte Technisch-Kognitive Systeme/en: Unterschied zwischen den Versionen
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==Open Theses and HiWi-Jobs== | ==Open Theses and HiWi-Jobs== | ||
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− | <th>< | + | <th><h3>Research Area</h3></th> |
− | <th>< | + | <th><h3>Research Topics</h3></th> |
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<li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> <br> | <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> <br> | ||
<li>[https://www.aifb.kit.edu/web/Daniel_Bogdoll Anomaly Detection for Autonomous Driving]</li> <br> | <li>[https://www.aifb.kit.edu/web/Daniel_Bogdoll Anomaly Detection for Autonomous Driving]</li> <br> | ||
+ | <li>[https://www.aifb.kit.edu/web/Marc_Uecker Deep Learning based 3D Environment Perception for Autonomous Vehicles]</li> <br> | ||
+ | <li>[https://www.aifb.kit.edu/web/Marc_Uecker Sensor-setup agnostic Machine Learning Perception for Autonomous Vehicles]</li> <br> | ||
<li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Robust, Interpretable and Energy-Efficient Deep Learning for Camera-based Perception]</li> <br> | <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Robust, Interpretable and Energy-Efficient Deep Learning for Camera-based Perception]</li> <br> | ||
<li>[https://www.aifb.kit.edu/web/Tobias_Fleck Sensorfusion for Connected Autonomous Driving]</li> <br> | <li>[https://www.aifb.kit.edu/web/Tobias_Fleck Sensorfusion for Connected Autonomous Driving]</li> <br> | ||
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<li>[https://www.aifb.kit.edu/web/Nikolai_Polley Predicting the Behavior of Traffic Participants with Deep Neural Networks]</li> <br> | <li>[https://www.aifb.kit.edu/web/Nikolai_Polley Predicting the Behavior of Traffic Participants with Deep Neural Networks]</li> <br> | ||
<li>[https://aifb.kit.edu/web/Philipp_Stegmaier Behavior and Motion Prediction of Traffic Participants for Safe Trajectory Planning]</li> <br> | <li>[https://aifb.kit.edu/web/Philipp_Stegmaier Behavior and Motion Prediction of Traffic Participants for Safe Trajectory Planning]</li> <br> | ||
− | <li>[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> | + | <li>[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> <br> |
+ | <li>[https://aifb.kit.edu/web/Albert_Lee A priori VRU Behavior Prediction using Traffic Infrastructure for Autonomous Driving]</li> | ||
</ul> | </ul> | ||
</td> | </td> | ||
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<td> | <td> | ||
<ul> | <ul> | ||
− | <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving] | + | <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> <br> |
− | <li></li> | + | <li>[https://aifb.kit.edu/web/Sven_Ochs Semantic LiDAR-Localization and Validation through GPS and Odometrie]</li> |
</ul> | </ul> | ||
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</tr> | </tr> | ||
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<td> <h4>End-to-end learning</h4> </td> | <td> <h4>End-to-end learning</h4> </td> | ||
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</td> | </td> | ||
</tr> | </tr> | ||
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<td> <h4>Mixed Reality</h4> </td> | <td> <h4>Mixed Reality</h4> </td> | ||
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</td> | </td> | ||
</tr> | </tr> | ||
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<td> <h4>Reinforcement Learning</h4> </td> | <td> <h4>Reinforcement Learning</h4> </td> | ||
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<td> | <td> | ||
<ul> | <ul> | ||
− | <li>[https://aifb.kit.edu/web/Maximilian_Zipfl Postprocessing of Trajectory Tracking]</li> | + | <li>[https://www.aifb.kit.edu/web/Helen_Schneider Automated Capturing of User Experience in Autonomous Vehicles]</li> <br> |
+ | <li>[https://aifb.kit.edu/web/Maximilian_Zipfl Postprocessing of Trajectory Tracking]</li> <br> | ||
+ | <li>[https://www.aifb.kit.edu/web/Marc_Uecker Vehicle Hardware and Sensor Setups for Autonomous Vehicles]</li> <br> | ||
<li></li> | <li></li> | ||
</ul> | </ul> |
Version vom 21. April 2023, 06:29 Uhr
Office: |
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.
Open Theses and HiWi-Jobs
|
Our Partner Institutes
- Ahmed Abouelazm
- Daniel Bogdoll
- Johannes Buyer
- Mohammd Karam Daaboul
- Jens Doll
- Marcus Fechner
- Tobias Fleck
- Martin Gontscharow
- Helen Gremmelmaier
- Daniel Grimm
- Dominik Heid
- Marc Heinrich
- Christian Hubschneider
- Tim Joseph
- Florian Kuhnt
- Karl Kurzer
- Nico Lambing
- Albert Lee
- Ferdinand Mütsch
- Sven Ochs
- Stefan Orf/en
- Stefan Orf
- Svetlana Pavlitskaya
- Nikolai Polley
- Rupert Polley
- Helen Schneider
- Albert Schotschneider
- Philip Schörner
- Philipp Stegmaier
- Marc Uecker
- Abhishek Vivekanandan
- Michael Weber
- Melih Yazgan
- Maximilian Zipfl
- Marc Zofka
- J. Marius Zöllner
- Advanced Programming - Java Network Programming, lecture (takes place in summer semester)
- Machine Learning 1 - Fundamental Methods, lecture (takes place in winter semester)
- Machine Learning 2 – Advanced Methods, lecture (takes place in summer semester)
- Programming I: Java, lecture (takes place in winter semester)
- Cognitive automobiles and robots, seminar (takes place in )
- Lab Course Cognitive Automobiles, practical course (takes place in winter semester)
- Lab Course Machine Learning, practical course (takes place in summer semester)
SPP 1835: Kooperativ interagierende Automobile |
SofDCar |
Testfeld Autonomes Fahren |