Angewandte Technisch-Kognitive Systeme/en: Unterschied zwischen den Versionen
Yf3851 (Diskussion | Beiträge) |
Yf3851 (Diskussion | Beiträge) |
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Zeile 43: | Zeile 43: | ||
<td> <h6>Perception</h6> </td> | <td> <h6>Perception</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Nikolai_Polley Traffic Light Detection with Deep Neural Networks for Autonomous Driving]</li> | |
− | <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[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 style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Daniel_Bogdoll Anomaly Detection for Autonomous Driving]</li> |
− | <li>[https://www.aifb.kit.edu/web/Marc_Uecker Deep Learning based 3D Environment Perception for Autonomous Vehicles]</li> | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Marc_Uecker Deep Learning based 3D Environment Perception for Autonomous Vehicles]</li> |
− | <li>[https://www.aifb.kit.edu/web/Marc_Uecker Sensor-setup agnostic Machine Learning Perception for Autonomous Vehicles]</li> | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Marc_Uecker Sensor-setup agnostic Machine Learning Perception for Autonomous Vehicles]</li> |
− | <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Robust, Interpretable and Energy-Efficient Deep Learning for Camera-based Perception]</li> | + | <li style="margin-bottom: 0.5em">[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/Tobias_Fleck Sensorfusion for Connected Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Tobias_Fleck Sensorfusion for Connected Autonomous Driving]</li> |
− | <li>[https://www.aifb.kit.edu/web/Tobias_Fleck Intelligent Roadside Infrastructure for Connected Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Tobias_Fleck Intelligent Roadside Infrastructure for Connected Autonomous Driving]</li> |
− | <li>[https://aifb.kit.edu/web/Stefan_Orf Recognition of Sensor Data Discrepancies in Autonomous Vehicles and Smart Infrastructure]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Stefan_Orf Recognition of Sensor Data Discrepancies in Autonomous Vehicles and Smart Infrastructure]</li> |
− | <li>[https://aifb.kit.edu/web/Melih_Yazgan Perception with Intelligent Traffic Infrastructure]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Melih_Yazgan Perception with Intelligent Traffic Infrastructure]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 60: | Zeile 60: | ||
<td> <h6>Prediction</h6> </td> | <td> <h6>Prediction</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Nikolai_Polley Predicting the Behavior of Traffic Participants with Deep Neural Networks]</li> | |
− | <li>[https://aifb.kit.edu/web/Philipp_Stegmaier/en Behavior and Motion Prediction of Traffic Participants for Safe Trajectory Planning]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Philipp_Stegmaier/en Behavior and Motion Prediction of Traffic Participants for Safe Trajectory Planning]</li> |
− | <li>[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> |
− | <li>[https://aifb.kit.edu/web/Albert_Lee A priori VRU Behavior Prediction using Traffic Infrastructure for Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Albert_Lee A priori VRU Behavior Prediction using Traffic Infrastructure for Autonomous Driving]</li> |
− | <li>[https://aifb.kit.edu/web/Ahmed_Abouelazm Trajectory forecasting under road topology and vehicle constraints]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Ahmed_Abouelazm Trajectory forecasting under road topology and vehicle constraints]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 72: | Zeile 72: | ||
<td> <h6>UX</h6> </td> | <td> <h6>UX</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Helen_Schneider Automated Capture of User Experience in Autonomous Vehicles]</li> | |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 80: | Zeile 80: | ||
<td> <h6>Maps</h6> </td> | <td> <h6>Maps</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Nico_Lambing Automated Generation and Maintenance of Probabilistic HD-Maps]</li> | |
− | <li>[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Rupert_Polley Aerial Image Segmentation with Deep Neural Networks for Autonomous Driving]</li> |
− | <li>[https://aifb.kit.edu/web/Sven_Ochs Semantic LiDAR-Localization and Validation through GPS and Odometrie]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Sven_Ochs Semantic LiDAR-Localization and Validation through GPS and Odometrie]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 90: | Zeile 90: | ||
<td> <h6>Planning</h6> </td> | <td> <h6>Planning</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Philipp_Stegmaier/en Cooperative Trajectory Planning under Uncertainties]</li> | |
− | <li>[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Philip_Sch%C3%B6rner Probabilistic Decision Making and Scene Interpretation]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 99: | Zeile 99: | ||
<td> <h6>Safety and Security</h6> </td> | <td> <h6>Safety and Security</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Albert_Schotschneider Misbehavior Detection and Optimization of Driving Components for Robustness Improvement]</li> | |
− | <li>[https://aifb.kit.edu/web/Albert_Schotschneider Evaluating Metrics for Performance Assessment in Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Albert_Schotschneider Evaluating Metrics for Performance Assessment in Autonomous Driving]</li> |
− | <li>[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Adversarial Attacks on Deep Learning Models]</li> | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Svetlana_Pavlitskaya Adversarial Attacks on Deep Learning Models]</li> |
− | <li>[https://aifb.kit.edu/web/Stefan_Orf Condition Monitoring for Robust and Safe Autonomous Systems]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Stefan_Orf Condition Monitoring for Robust and Safe Autonomous Systems]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 110: | Zeile 110: | ||
<td> <h6>Vehicle-to-Everything (V2X/Car2X)</h6> </td> | <td> <h6>Vehicle-to-Everything (V2X/Car2X)</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[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 style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Martin_Gontscharow Interactive Machine Learning for Remote Assisted Autonomous Vehicles]</li> |
− | <li>[https://aifb.kit.edu/web/Stefan_Orf Remote Operation in Autonomous Driving]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Stefan_Orf Remote Operation in Autonomous Driving]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 120: | Zeile 120: | ||
<td> <h6>Simulation</h6> </td> | <td> <h6>Simulation</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Marc_Zofka Distributed Virtual Reality (VR) and Simulation Frameworks for Validation and Verification of Autonomous Vehicles]</li> | |
− | <li>[https://aifb.kit.edu/web/Helen_Gremmelmaier Simulation of Autonomous Driving and Behaviour Modelling of Vulnerable Road Users]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Helen_Gremmelmaier Simulation of Autonomous Driving and Behaviour Modelling of Vulnerable Road Users]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 130: | Zeile 130: | ||
<td> <h6>End-to-end learning</h6> </td> | <td> <h6>End-to-end learning</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em"></li> | |
− | <li></li> | + | <li style="margin-bottom: 0.5em"></li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 139: | Zeile 139: | ||
<td> <h6>Mixed Reality</h6> </td> | <td> <h6>Mixed Reality</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em"></li> | |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 148: | Zeile 148: | ||
<td> <h6>Reinforcement Learning</h6> </td> | <td> <h6>Reinforcement Learning</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Tim_Joseph Efficient Unsupervised Reinforcement Learning]</li> | |
− | <li>[https://aifb.kit.edu/web/Ahmed_Abouelazm End-to-End autonomous driving using Reinforcement Learning]</li> | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Ahmed_Abouelazm End-to-End autonomous driving using Reinforcement Learning]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
Zeile 157: | Zeile 157: | ||
<td> <h6>Other Topics in Autonomous Driving</h6> </td> | <td> <h6>Other Topics in Autonomous Driving</h6> </td> | ||
<td> | <td> | ||
− | <ul style=" | + | <ul> |
− | + | <li style="margin-bottom: 0.5em">[https://aifb.kit.edu/web/Maximilian_Zipfl Postprocessing of Trajectory Tracking]</li> | |
− | <li>[https://www.aifb.kit.edu/web/Marc_Uecker Vehicle Hardware and Sensor Setups for Autonomous Vehicles]</li> | + | <li style="margin-bottom: 0.5em">[https://www.aifb.kit.edu/web/Marc_Uecker Vehicle Hardware and Sensor Setups for Autonomous Vehicles]</li> |
</ul> | </ul> | ||
</td> | </td> | ||
</tr> | </tr> | ||
</table> | </table> | ||
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Version vom 4. August 2023, 09:37 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.
- 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
- Stefan Orf/en
- 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)
C2CBridge |
SPP 1835: Kooperativ interagierende Automobile |
SofDCar |
Testfeld Autonomes Fahren |