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 and Jan Babic was accepted for publication at IEEE Robotics and Automation Letters (RA-L).
Archives
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).
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 contribute to the data science master program.
Successful Graduation of Daniel Tanneberg
Congratulations to Daniel Tanneberg for completing his PhD. He is the first graduate of Prof. Elmar Rueckert’s group.
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 (2019).
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 SENSORS 2020 Conference, to be held from October 25-28, 2020.
Conference Paper accepted at BMT2020
The paper by Tolga-Can Çallar, Elmar Rueckert and Sven Böttger on “Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates” was accepted for publication in the 54th Annual Conference of the German Society for Biomedical Engineering (BMT 2020).
.
Workshop accepted at IROS 2020
Our workshop on „New Horizons for Robot Learning“ was accepted at the International Conference on Intelligent Robots and Systems (IROS’ 2020). See https://iros.ai-lab.science
Conference Paper accepted at IROS 2020
The paper by Nils Rottmann, Tjaša Kunavar, Jan Babič, Jan Peters and Elmar Rueckert on “Learning Hierarchical Acquisition Functions for Bayesian Optimization” was accepted for publication at the International Conference on Intelligent Robots and Systems (IROS’ 2020).
Proceedings of Machine Learning Research Paper accepted
E. Cartoni, F. Mannella, V.G. Santucci, J. Triesch, E. Rueckert, G. Baldassarre. REAL-2019: Robot open-Ended Autonomous Learning competition. Proceedings of Machine Learning Research 123:142-152, 2020. NeurIPS 2019 Competition and Demonstration Track