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 Stimulation” at the journal Frontiers in Robotics and AI in September 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 Mobile Robotics (ECMR).

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

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

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 and Jan Babic was accepted for publication at IEEE Robotics and Automation Letters (RA-L).

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).

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.