Angewandte Technisch-Kognitive Systeme/en: Unterschied zwischen den Versionen
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+ | |width="80px" style="vertical-align:top;"|15.11.2018 | ||
+ | |[[Neuigkeit111|Audi Autonomous Driving Cup 2018: Team AlpaKa wins the titel]] | ||
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+ | |width="80px" style="vertical-align:top;"|05.11.2018 | ||
+ | |[[Neuigkeit108|Best Paper Award - IEEE International Conference on Intelligent Transportation Systems (ITSC)]] | ||
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+ | |width="80px" style="vertical-align:top;"|28.06.2018 | ||
+ | |[[Neuigkeit110|Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)]] | ||
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+ | |width="80px" style="vertical-align:top;"|28.06.2018 | ||
+ | |[[Neuigkeit109|Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)]] | ||
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+ | __NOTOC__ | ||
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+ | =====Open Thesis Projects===== | ||
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+ | =====Open Positions===== | ||
+ | [http://www.aifb.kit.edu/web/Stellenausschreibung114 Student Assistant | Cooperatively Interacting Automobiles] | ||
+ | |||
+ | [http://www.aifb.kit.edu/web/Stellenausschreibung134 Student Assistant | Systemadministration] | ||
+ | |||
+ | [http://www.aifb.kit.edu/web/Stellenausschreibung115/en Research Scientist | Highly Automated Driving] | ||
+ | |||
+ | =====Our Partner Institutes===== | ||
+ | :{{#tag:imagemap | Bild:Fzilogo.gif{{!}}45px | ||
+ | default [http://www.fzi.de] | ||
+ | desc none | ||
+ | }} | ||
+ | :[http://www.fzi.de/wir-ueber-uns/organisation/forschungsbereiche/ispe/ Forschungsbereich ISPE] | ||
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+ | <!--Nur TKS spezifische events sollen angezeigt werden {{Forschungsgruppe Konferenzen und Workshops|Sprache=DE}} --> | ||
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Aktuelle Version vom 24. Februar 2021, 16:15 Uhr
= Applied Technical Cognitive Systems=
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 Thesis ProjectsTitle: Deep Reinforcement Learning for Autonomous Driving Title: Thinking Fast and Slow with Model-Based Reinforcement Learning Title: Deep Reinforcement Learning for the Control of Robotic Manipulation Title: Efficient Uncertainty Aware Latent Model-Based Optimization Title: Machine Learning & Transfer Learning im Bereich der Arbeitsmaschinen Title: Manöver- / Trajektorienplanung unter Unsicherheiten
Open PositionsStudent Assistant | Cooperatively Interacting Automobiles Student Assistant | Systemadministration Research Scientist | Highly Automated Driving Our Partner Institutes |
- Daniel Bogdoll
- Johannes Buyer
- Mohammd Karam Daaboul
- Jens Doll
- Marcus Fechner
- Tobias Fleck
- Daniel Grimm
- Marc Heinrich
- Christian Hubschneider
- Tim Joseph
- Florian Kuhnt
- Karl Kurzer
- Nico Lambig
- Sven Ochs
- Stefan Orf
- Svetlana Pavlitskaya
- Nikolai Polley
- Albert Schotschneider
- Philip Schörner
- Philipp Stegmaier
- Lars Töttel
- Abhishek Vivekanandan
- Michael Weber
- Maximilian Zipfl
- Marc Zofka
- J. Marius Zöllner
- 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)
- 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 |
Testfeld Autonomes Fahren |