The Chair of Cyber-Physical-Systems
The Chair of Cyber-Physical-Systems at the Montanuniversität Leoben in Austria is headed by Prof. Elmar Rueckert.
The group’s research topics are autonomous systems, machine and deep learning, embedded smart sensing systems, and computational models.
Latest Research Videos
AI & Robotics Positions and Topics
The chair is offering a number of open positions and student thesis topics in AI and robotics.
Also check our wiki, which offers numerous public posts on open source code repositories or tutorials.
Latest news
News
September 29, 2022
Conference Paper accepted at HUMANOIDS 2022
The paper on Predicting full-arm grasping motions from anticipated tactile responsess by Dave Vedant and Rueckert Elmar was accepted for publication at the International Conference on Humanoid Robots (Humanoids 2022),..Read MoreSeptember 20, 2022
Journal Paper Accepted at Frontiers in Neuroscience
The paper by Rebecca Herzog and Till M Berger and Martje Gesine Pauly and Honghu Xue and Elmar Rueckert and Alexander Munchau and Tobias Bäumer and Anne Weissbach on “Cerebellar..Read MoreMarch 17, 2022
Journal Paper Accepted at Applied Sciences MDPI
The paper by Honghu Xue and Benedikt Hein and Mohamed Bakr and Georg Schildbach and Bengt Abel and Elmar Rueckert on “Using Deep Reinforcement Learning with Automatic Curriculum Learning for..Read MoreMarch 1, 2022
Successful grant
Our grant application for building an AI Robot Lab was funded. We will set up an industrial robot learning lab with two universal robotics UR3e arms, two FANUC CRX10iA robot..Read MoreOctober 6, 2021
Conference Paper accepted at ICAR 2021
The paper on A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning by Robin Denz*, Rabia Demirci, Mehmet Ege Cansev, Adna Bliek, Beckerle Beckerle, Elmar Rueckert and Nils Rottmann was accepted..Read MoreSeptember 14, 2021
Journal Paper accepted at Frontiers in Robotics and AI
Xue Honghu, Herzog Rebecca, Berger Till M., Bäumer Tobias, Weissbach Anne and Rueckert Elmar published the article on “Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current..Read MoreJuly 20, 2021
Conference Paper accepted at ECMR 2021
The paper by Nils Rottmann, Robin Denz, Ralf Bruder and Elmar Rueckert on “Probabilistic Approach for Complete Coverage Path Planning with low-cost Systems” was accepted at the European Conference on..Read MoreMay 7, 2021
Conference Paper accepted at HUMANOIDS 2021
The paper by Marko Jamsek, Tjasa Kunavar, Urban Bobek, Elmar Rueckert and Jan Babic on Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow..Read MoreMarch 11, 2021
Journal paper of the DFG TRAIN project team accepted
The paper on “Interactive Human-Robot Skill Transfer: A Review of Learning Methods and User Experience” by Mehmet Ege Cansev, Honghu Xue, Nils Rottmann, Adna Bliek, Luke E. Miller, Elmar Rueckert..Read MoreMarch 11, 2021
Journal Paper accepted at IEEE RA-L
The paper on “SKID RAW: Skill Discovery from Raw Trajectories“, by Daniel Tanneberg, Kai Ploeger, Elmar Rueckert, Jan Peters was accepted for publication at IEEE Robotics and Automation Letters(RA-L).March 11, 2021
Journal Paper accepted at IEEE RA-L
The paper “Predictive exoskeleton control for arm-motion augmentation based on probabilistic movement primitives combined with a flow controller” by Marko Jamsek and Tjasa Kunavar and Urban Bobek and Elmar Rueckert..Read MoreMarch 3, 2021
1st of March 2021 Starting as Chair of the Cyber-Physical-Systems Lab at Leoben
With March 1st, 2021, Prof. Rueckert chairs the Cyber-Physic al-Systems Institute at the Montanuniversität in Leoben, Austria. This new Institute will focus on robotics and machine learning research and will..Read MoreDecember 3, 2020
Successful Graduation of Daniel Tanneberg
Congratulations to Daniel Tanneberg for completing his PhD. He is the first graduate of Prof. Elmar Rueckert’s group.October 20, 2020
Journal Paper accepted at IEEE Sensors Journal
Nils Rottmann, Ralf Bruder, Achim Schweikard, Elmar Rueckert A novel Chlorophyll Fluorescence based approach for Mowing Area Classification accepted (Oct, 12th 2020) at IEEE Sensors Journal with an Impact Factor of 3..Read MoreAugust 28, 2020
Conference Paper Accepted at IEEE Sensors
The paper by Nils Rottmann, Ralf Burder, Achim Schweikard und Elmar Rueckert on Exploiting Chlorophyll Fluorescense for Building Robust low-Cost Mowing Area Detectors was accepted for publication at the IEEE..Read MoreMore news on Professor Rueckert’s page.