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{|
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|width="80px" style="vertical-align:top;"|15.11.2018
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|[[Neuigkeit111|Audi Autonomous Driving Cup 2018: Team AlpaKa wins the titel]]
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|width="80px" style="vertical-align:top;"|05.11.2018
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|[[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
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|[[Neuigkeit110|Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)]]
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|width="80px" style="vertical-align:top;"|28.06.2018
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|[[Neuigkeit109|Best Paper Award - IEEE Intelligent Vehicles Symposium (IV)]]
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==Open Theses and HiWi-Jobs==
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<table style="width:90%">
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  <tr style="border-bottom: 1px solid #ddd">
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    <th><h3>Research Area</h3></th>
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    <th><h3>Research Topics</h3></th>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Perception</h4> </td>
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    <td>
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      <ul>
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        <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> <br>
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        <li>[https://www.aifb.kit.edu/web/Daniel_Bogdoll Anomaly Detection for Autonomous Driving]</li> <br>
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        <li>[https://www.aifb.kit.edu/web/Marc_Uecker Deep Learning based 3D Environment Perception for Autonomous Vehicles]</li> <br>
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        <li>[https://www.aifb.kit.edu/web/Marc_Uecker Sensor-setup agnostic Machine Learning Perception for Autonomous Vehicles]</li> <br>
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        <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Robust, Interpretable and Energy-Efficient Deep Learning for Camera-based Perception]</li> <br>
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        <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/Tobias_Fleck Intelligent Roadside Infrastructure for Connected Autonomous Driving]</li> <br>
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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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      </ul>
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    </td>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Prediction</h4> </td>
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    <td>
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      <ul>
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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>
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        <li>[https://aifb.kit.edu/web/Philipp_Stegmaier Behavior and Motion Prediction of Traffic Participants for Safe Trajectory Planning]</li> <br>
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        <li>[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> <br>
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        <li>[https://aifb.kit.edu/web/Albert_Lee A priori VRU Behavior Prediction using Traffic Infrastructure for Autonomous Driving]</li>
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      </ul>
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    </td>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Maps</h4> </td>
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    <td>
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      <ul>
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        <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> <br>
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        <li>[https://aifb.kit.edu/web/Sven_Ochs Semantic LiDAR-Localization and Validation through GPS and Odometrie]</li>
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      </ul>
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    </td>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Planning</h4> </td>
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    <td>
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      <ul>
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        <li>[https://aifb.kit.edu/web/Philipp_Stegmaier Cooperative Trajectory Planning under Uncertainties]</li> <br>
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        <li>[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li>
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      </ul>
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    </td>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Safety and Security</h4> </td>
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    <td>
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      <ul>
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        <li>[https://aifb.kit.edu/web/Albert_Schotschneider Misbehavior Detection and Optimization of Driving Components for Robustness Improvement]</li> <br>
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        <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Adversarial Attacks on Deep Learning Models]</li> <br>
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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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      </ul>
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    </td>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Vehicle-to-Everything (V2X/Car2X)</h4> </td>
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    <td>
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      <ul>
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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> <br>
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        <li>[https://aifb.kit.edu/web/Martin_Gontscharow Interactive Machine Learning for Remote Assisted Autonomous Vehicles]</li> <br>
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        <li>[https://aifb.kit.edu/web/Stefan_Orf Remote Operation in Autonomous Driving]</li>
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      </ul>
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    </td>
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  </tr>
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  <tr style="border-bottom: 1px solid #ddd">
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    <td> <h4>Simulation</h4> </td>
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    <td>
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      <ul>
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        <li>[https://www.aifb.kit.edu/web/Marc_Zofka Distributed Virtual Reality (VR) and Simulation Frameworks for Validation and Verification of Autonomous Vehicles]</li> <br>       
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<li>[https://aifb.kit.edu/web/Helen_Gremmelmaier Simulation of Autonomous Driving and Behaviour Modelling of Vulnerable Road Users]</li>
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      </ul>
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    </td>
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  </tr>
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    <td> <h4>End-to-end learning</h4> </td>
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    <td>
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      <ul>
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        <li></li>
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        <li></li>
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      </ul>
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    </td>
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    <td> <h4>Mixed Reality</h4> </td>
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    <td>
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    <td> <h4>Reinforcement Learning</h4> </td>
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    <td>
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      <ul>
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        <li>[https://aifb.kit.edu/web/Tim_Joseph Efficient Unsupervised Reinforcement Learning]</li>
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        <li></li>
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      </ul>
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    </td>
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  </tr>
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  <tr>
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    <td> <h4>Other Topics in Autonomous Driving</h4> </td>
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    <td>
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      <ul>
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        <li>[https://www.aifb.kit.edu/web/Helen_Schneider Automated Capturing of User Experience in Autonomous Vehicles]</li> <br>
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        <li>[https://aifb.kit.edu/web/Maximilian_Zipfl Postprocessing of Trajectory Tracking]</li> <br>
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        <li>[https://www.aifb.kit.edu/web/Marc_Uecker Vehicle Hardware and Sensor Setups for Autonomous Vehicles]</li> <br>
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        <li></li>
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      </ul>
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    </td>
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  </tr>
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</table>
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====Our Partner Institutes====
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:[http://www.fzi.de/wir-ueber-uns/organisation/forschungsbereiche/ispe/ Intelligent Systems and Production Engineering]
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Aktuelle Version vom 21. April 2023, 06:29 Uhr


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Office:
 
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
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

Reinforcement Learning

Other Topics in Autonomous Driving



Our Partner Institutes

Fzilogo.gif
Intelligent Systems and Production Engineering



People



Courses


Active Projects
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SPP 1835: Kooperativ interagierende Automobile
External Link: http://www.coincar.de/#/

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SofDCar
External Link: https://www.sofdcar.de

Taf logo transparent.png

Testfeld Autonomes Fahren
External Link: https://taf-bw.de/


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