Our AI Lab in Berlin offers the ideal framework and conditions for performing outstanding applied research in various AI topics such as Generative AI, Computer Vision, Explainable & Safe AI, Data for AI, Motion Planning for autonomous systems such as vehicles and robots, and Natural Language Processing. Our international team of AI experts, PhD candidates and Master students closely cooperate with experts from a wide range of corporate divisions to bridge the gap between research and application and to empower Continental through cutting-edge AI technologies. Located at the Merantix AI Campus in Berlin, we also benefit from contacts and cooperation with other AI companies and research institutions.
Continental AI Lab Berlin
Who we are
What we do
At our AI Lab in Berlin, we are currently working on four main projects.
BeIntelli
In the BeIntelli project, our AI Lab robotics team works on the Continental AMR (autonomous mobile robots) development prototype for operation in public spaces. The robot is operated by our AI-based software stack for perception, localization, and navigation as well as safety. It is the first fully automated AMR to have ever obtained a driving permission for public areas in Berlin, including the busy Kurfürstendamm and Otto-Suhr-Allee boulevards.
Just Better Data (jbD)
The Just better Data project’s aim is to create AI-driven methods and tools for gathering data efficiently and accurately. Instead of producing excessive amounts of data, the focus is on processing, evaluating, and selecting data directly on the recording vehicle's edge. AI algorithms are employed to identify missing data and fill them in with synthetic data, ensuring a fair and characteristic dataset.
nxtAIM
nxtAIM utilizes the massive potential of generative technologies to develop new approaches for better scalability, transferability, and traceability of autonomous driving functions that, so far, have been very limited in their scope of use. The focus is on developing generative methods that are complementary to the established discriminative methods of artificial intelligence.
KI Wissen
In KI Wissen (AI Knowledge) projects, we developed and investigated methods for integrating existing knowledge into the data-driven AI functions of autonomous vehicles. The goal of the project is to create a comprehensive ecosystem for the integration of knowledge into the training and safeguarding of AI functions, thereby completely redefining the basis for training and validating of AI functions.
- Bouzidi, M.-K., Derajic, B., Goehring, D., Reichardt, J. Motion Planning under Uncertainty: Integrating Learning-Based Multi-Modal Predictors into Branch Model Predictive Control. In the International Conference on Intelligent Transportation Systems (ITSC-2024)
- Bouzidi, M.-K., Yao, Y., Goehring, D., Reichardt, J. Learning-Aided Warmstart of Model Predictive Control in Uncertain Fast-Changing Traffic. In the International Conference on Robotics and Automation (ICRA).
- Manas K., Zwicklbauer, S., Paschke, A. LLM based framework for Metric Temporal Logic Formalization of Traffic Rules. In the 2024 IEEE Intelligent Vehicles Symposium (IV).
- Mikriukov, G., Schwalbe, G., Motzkus, F., Bade, K. Unveiling the Anatomy of Adversarial Attacks: Concept-Based XAI Dissection of CNNs. In the 2nd World Conference on Explainable AI (xAI-2024).
- Motzkus, F., Mikriukov, G., Hellert, C., Schmid, U. Locally Testing Model Detections for Semantic Global Concepts. In xAI-2024.
- Sbeyti, M. K., Karg, M., Wirth C., Klein, N., Albayrak, S. Cost-Sensitive Uncertainty-Based Failure Recognition for Object Detection. In the Uncertainty in AI Conference (UAI).
- Schlauch, C., Wirth, C., Klein, N. Informed Spectral Normalized Gaussian Processes for Trajectory Prediction (Preprint). In ECAI-2024
- Shoeb, Y., Chan, R., Schwalbe, G., Nowzad, A., Güney, F., Gottschalk, H. Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles From Driving Scenes. In the Winter Conference on Applications of Computer Vision (WACV-2024).
- Chakraborty, T., Wirth, C., Seifert, C. Post-hoc Rule Based Explanations for Black Box Bayesian Optimization. In ECAI 2023 International Workshops.
- Kesser, M. Real-Time Explainable Plausibility Verification for DNN-based Automotive Perception. In the 1st World Conference on Explainable AI xAI-2023 & Late-breaking Work, Demos and Doctoral Consortium Joint Proceedings.
- Manas, K. and Paschke, A. Semantic Role Assisted Natural Language Rule Formalization for Intelligent Vehicle. In the International Joint Conference on Rules and Reasoning.
- Manas, K. and Paschke, A. Legal Compliance Checking of Autonomous Driving with Formalized Traffic Rule Exceptions. In Workshop on Logic Programming and Legal Reasoning in conjunction with 39th International Conference on Logic Programming (ICLP).
- Mikriukov, G., Schwalbe, G., Hellert, C., Bade, K. Revealing Similar Semantics Inside CNNs: An Interpretable Concept-based Comparison of Feature Spaces. In the AIMLAI 2023 Workshop in conjunction with ECML-PKDD.
- Mikriukov, G., Schwalbe, G., Hellert, C., Bade, K. Evaluating the Stability of Semantic Concept Representations in CNNs for Robust Explainability. In the 1st World Conference on Explainable AI (xAI-2023).
- Sbeyti, M. K., Karg, M., Wirth C., Nowzad, A., Albayrak, S. Overcoming the Limitations of Localization Uncertainty: Efficient & Exact Non-Linear Post-Processing and Calibration. In ECML-PKDD 2023, Research Track.
- Schlauch, C., Wirth, C., Klein, N. Informed Priors for Knowledge Integration in Trajectory Prediction. ECML-PKDD 2023, Research Track
- Yao, Y., Goehring, D., Reichardt, J. An Empirical Bayes Analysis of Object Trajectory Models. In the International Conference on Intelligent Transportation Systems (ITSC 2023)
Our AI Experts
Dr. Andreas Weinlich
Head of Laboratory for AI
Dr. Kostadin Cholakov
Technical Project Lead for AI
Dr. Azarm Nowzad
Technical Project Lead for AI
Dr. Sebastian Bernhard
Technical Project Lead
Simon Kast
AI Robotics Engineer
Our PhD Candidates - AI Research Scientists
Aditi Bhalla
Bojan Derajic
Christian Schlauch
Franz Motzkus
Georgii Mikriukov
Jonas Neuhöfer
Kumar Manas
Marius Kästingschäfer
Mert Keser
Mohamed-Khalil Bouzidi
Moussa Kassem Sbeyti
Pallavi Mitra
Tanmay Chakraborty
Youssef Shoeb
