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 controller was accepted at the IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids).

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 and Philipp Beckerle was accepted for publication at the Advanced Intelligent Systems.

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).

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).

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.

Congratulations to Daniel Tanneberg for completing his PhD. He is the first graduate of Prof. Elmar Rueckert’s group.

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).

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.

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).

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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