Elmar Rückert
Research output
- 2022
- Published
End-To-End Deep Reinforcement Learning for First-Person Pedestrian Visual Navigation in Urban Environments
Xue, H., Song, R., Petzold, J., Hein, B., Hamann, H. & Rueckert, E., 26 Sept 2022, IEEE-RAS International Conference on Humanoid Robots. (IEEE-RAS International Conference on Humanoid Robots).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Predicting full-arm grasping motions from anticipated tactile responses
Dave, V. & Rueckert, E., 26 Sept 2022, IEEE-RAS International Conference on Humanoid Robots. (IEEE-RAS International Conference on Humanoid Robots).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- Published
Cerebellar transcranial current stimulation: An intraindividual comparison of different techniques
Herzog, R., Berger, T. M., Pauly, M. G., Xue, H., Rückert, E., Münchau, A., Bäumer, T. & Weissbach, A., 15 Sept 2022, In: Frontiers in Neuroscience. 16, 12 p., 987472.Research output: Contribution to journal › Article › Research › peer-review
- Published
Using Deep Reinforcement Learning with Automatic Curriculum Learning for Mapless Navigation in Intralogistics
Xue, H., Hein, B., Bakr, M., Schildbach, G., Abel, B. & Rueckert, E., 19 Mar 2022, In: Applied Sciences : open access journal. 12.2022, 6, 30 p., 3153.Research output: Contribution to journal › Article › Research › peer-review
- 2021
- Published
A high-accuracy, low-budget Sensor Glove for Trajectory Model Learning
Denz, R., Demirci, R., Cansev, M. E., Bliek, A., Beckerle, P., Rueckert, E. & Rottmann, N., 6 Dec 2021, In: Proceedings of the International Conference on Advanced Robotics. p. 1109-1115 7 p.Research output: Contribution to journal › Conference article › peer-review
- Published
Using Probabilistic Movement Primitives in Analyzing Human Motion Differences Under Transcranial Current Stimulation
Xue, H., Herzog, R., Berger, T. M., Bäumer, T., Weissbach, A. & Rueckert, E., 14 Sept 2021, In: Frontiers in robotics and AI. 8.2021, 18 p., 721890.Research output: Contribution to journal › Article › Research › peer-review
- Published
A probabilistic approach for complete coverage path planning with low-cost systems
Rottmann, N., Denz, R., Bruder, R. & Rueckert, E., Aug 2021, 2021 10th European Conference on Mobile Robots, ECMR 2021 - Proceedings. Institute of Electrical and Electronics Engineers, (2021 10th European Conference on Mobile Robots, ECMR 2021 - Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Chapter › Research
- Published
SKID RAW: Skill Discovery from Raw Trajectories
Tanneberg, D., Ploeger, K., Rueckert, E. & Peters, J., Jul 2021, In: IEEE robotics and automation letters. 6, 3, p. 4696-4703 8 p., 9387162.Research output: Contribution to journal › Article › Research › peer-review
- Published
Interactive Human–Robot Skill Transfer: A Review of Learning Methods and User Experience
Cansev, M. E., Xue, H., Rottmann, N., Bliek, A., Miller, L. E., Rückert, E. & Beckerle, P., 6 May 2021, In: Advanced Intelligent Systems. 3.2021, 7, 11 p., 2000247.Research output: Contribution to journal › Article › Research › peer-review
- E-pub ahead of print
Predictive Exoskeleton Control for Arm-Motion Augmentation Based on Probabilistic Movement Primitives Combined with a Flow Controller
Jamsek, M., Kunavar, T., Bobek, U., Rueckert, E. & Babic, J., 25 Mar 2021, (E-pub ahead of print) In: IEEE robotics and automation letters. 6.2021, 3, p. 4417-4424 8 p., 9387088.Research output: Contribution to journal › Article › Research › peer-review
