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Poster on "Mid-term status report on KISSaF" to be presented at AmE 2022.
AmE (Automotive meets Electronics) 2022 will be held at the Westfalenhallen in Dortmund, Germany, from September 29-30, 2022. At the conference, the…
Successful 17th DortmunderAutoTag in presence
After the successful 17th DortmunderAutoTag, which could again take place in presence, we would like to thank all speakers, exhibitors and…
RST attended the IHIET Conference 2022
This year, RST attended the IHIET Conference 2022 and reported on the latest achievements in Driver Activity Recognition using pressure sensor…
First measurement ride as part of the DEmandäR project
On a rainy Friday, we started the first measurement ride with our research vehicle at our partner Stadwerke Menden as part of the publicly funded…
collaboration between humans and robots
Thanks to funding from the German Research Foundation, we are continuing to investigate collaboration between humans and robots. The focus here is on…
Occlusion resolving with GANs
We made progress in spatio-temporal reasoning for occlusion resolving with Generative Adversarial Networks, a powerful generative Deep Learning model.
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Interim presentation on the KISSaF project at TU-Dortmund
On June 09, 2022, in the Rudolf Chaudoire Pavilion of the TU Dortmund University, the midterm presentation of the project KISSaF - AI-based Situation…
Congratulations to Mr Lienke
We congratulate Mr Christian Lienke on his successfully completed doctorate "Trajectory Planning for Automated Driving in Dynamic Environments"
© RST/TU-Dortmund
The Institute of Control Theory and Systems Engineering at TU Dortmund University conducts research on automated, networked and sustainable mobility and service robotics in both basic and application-oriented topics.
The innovative research process begins with the idea, continues with scientific analysis and synthesis and ends in the engineering context with feasibility and/or a prototype. The scientists contribute their ideas, competences and experience to public and bilateral research and development projects.
In the topics of future mobility, our research focuses on scene description, situation prediction including trajectory prediction and manoeuvre planning decision making when it comes to the movement behaviour of the EGO vehicle and other road users.
In situational prediction and manoeuvre planning, the behaviour and the physical and mental state of the driver, passenger and passer-by are also researched and taken into account in the overall planning for automated driving.
In service robotics, the cooperation between humans and robots is the focus of our research. We develop concepts and methods for model-predictive real-time trajectory planning and control in a shared workspace. In lightweight robotics, we design models and controls for limb-elastic robot arms.
The research work is oriented towards concrete questions, which are evaluated concomitantly in x-in-the-loop simulation and finally in prototype testing, in order to also answer questions that go beyond scientific verification and validation from the perspective of application and technical realisation.
In the field of automated driving, methods from the areas of machine and deep learning as well as artificial intelligence are increasingly gaining acceptance - in all areas of development, from perception to trajectory planning and control. In addition to the development of the latest algorithms in this area, we also have the necessary hardware and the latest technical requirements to be able to quickly apply the aforementioned methods to new problems with maximum efficiency.
Another focus is on the development and application of forward-looking methods for the systematic derivation and development of solutions that meet requirements, without losing sight of the overall system.