Elmar Rückert
21 - 30 out of 61Page size: 10
Research output
Stochastic Optimal Control Methods for Investigating the Power of Morphological Computation
Rückert, E. A. & Neumann, G., Jan 2013, In: Artificial Life. 19.2013, 1, p. 115–131 17 p.Research output: Contribution to journal › Article › Research › peer-review
Learned graphical models for probabilistic planning provide a new class of movement primitives
Rückert, E. A., Neumann, G., Toussaint, M. & Maass, W., 2 Jan 2013, (E-pub ahead of print) In: Frontiers in computational neuroscience. 6.2013, January, 20 p., 97.Research output: Contribution to journal › Article › Research › peer-review
Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems
Rückert, E. & d'Avella, A., 17 Oct 2013, In: Frontiers in computational neuroscience. 7.2013, October, 18 p.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
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
Loop closure detection in closed environments
Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., Sept 2019.Research output: Contribution to conference › Paper › peer-review
- Published
Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors
Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., 2019, p. 214-223. 10 p.Research output: Contribution to conference › Paper › 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
- Published
Learning hierarchical acquisition functions for bayesian optimization
Rottmann, N., Kunavar, T., Babic, J., Peters, J. & Rueckert, E., 24 Oct 2020, IEEE International Conference on Intelligent Robots and Systems. p. 5490-5496 7 p. (IEEE International Conference on Intelligent Robots and Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Probabilistic movement primitives under unknown system dynamics
Paraschos, A., Rueckert, E., Peters, J. & Neumann, G., 25 Apr 2018, (E-pub ahead of print) In: Advanced robotics. 32.2018, 6, p. 297-310 14 p.Research output: Contribution to journal › Article › Research › peer-review
