Discover our interesting
On 07.09. the 18th DortmunderAutoTag took place in the IHKzuDortmund! We would like to thank all speakers, exhibitors and participants for their great…
Virtual lab tour
We are working on the presentation of our experimental systems on Youtube. The first videos are already available online, more will follow in the next…
Review of 3D point cloud object detectors for imaging radar sensor data.
Our contribution on reviewing 3D Point Cloud Object Detectors for Imaging Radar sensor data was presented on the 3D Vision and Robotics Workshop at…
DDPM-based multimodal point cloud prediction approach.
Learning-based trajectory predictions require elaborately generated data sets. Prediction from raw data, where no manual annotation is required,…
Heiko Renz awarded the Hans Uhde Prize
Heiko Renz, research assistant at the Chair of Control Systems Engineering, has been awarded the Hans-Uhde Prize 2023 as one of four graduates of the…
Successfully completed doctorate
We congratulate Mr. Andreas Homann on his successfully completed Ph. "Trajectory following control for automated vehicles - Investigations for a…
Filming in the laboratory area of the IRF
A team of the rehabilitation sciences of the TU Dortmund and the design department of the FH Dortmund made a film in our lab with director Florian…
Paper on 3D Radar object detection got accepted by the CVPR 2023
We are glad our paper on 3D Radar object detection got accepted by the CVPR 2023 Workshop on 3D Vision & Robotics.
First results look promising, but…
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.