Chair of Cyber Physical Systems (190)
Organisational unit: Chair
Research output
- 2021
- Published
Orientation Probabilistic Movement Primitives on Riemannian Manifolds
Rozo, L. & Dave, V., 8 Nov 2021, Conference on Robot Learning. 5 ed. Vol. 164. p. 373-383 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- 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
- Published
A novel chlorophyll fluorescence-based approach for mowing area classification
Rottmann, N., Bruder, R., Schweikard, A. & Rückert, E., 15 Feb 2021, In: IEEE sensors journal. 21, 4, p. 4500-4508 9 p., 9234496.Research output: Contribution to journal › Article › Research › peer-review
- Published
KI 2021: Advances in Artificial Intelligence - Preface
Edelkamp, S., Möller, R. & Rückert, E., 2021, KI 2021: Advances in Artificial Intelligence: 44th German Conference on AI, Virtual Event, September 27 – October 1, 2021, Proceedings. Edelkamp, S., Möller, R. & Rückert, E. (eds.). Vol. 12873 LNAI. p. v-vi (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
- 2020
- Published
Evolutionary training and abstraction yields algorithmic generalization of neural computers
Tanneberg, D., Rückert, E. & Peters, J., 16 Nov 2020, In: Nature machine intelligence.Research output: Contribution to journal › Article › Research › peer-review
- Published
Exploiting Chlorophyll Fluorescense for building robust low-cost Mowing Area Detectors
Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., 25 Oct 2020.Research output: Contribution to conference › Paper › peer-review
