Elmar Rückert
Research output
- 2020
- 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
Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates
Çallar, T. C., Rueckert, E. & Böttger, S., 1 Sept 2020, In: Current directions in biomedical engineering. 6.2020, 3, 4 p., 20203031.Research output: Contribution to journal › Article › Research › peer-review
Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control
Rückert, E., Čamernik, J., Peters, J. & Babič, J., 16 Apr 2020, In: Scientific reports (e-only). 6.2016, 1, 12 p., 28455 / 6694.Research output: Contribution to journal › Article › Research › peer-review
- 2019
- Published
Experience Reuse with Probabilistic Movement Primitives
Stark, S., Peters, J. & Rueckert, E., Nov 2019, IEEE International Conference on Intelligent Robots and Systems. p. 1210-1217 8 p. (IEEE International Conference on Intelligent Robots and Systems).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Medical robotics simulation framework for application-specific optimal kinematics
Böttger, S., Çallar, T. C., Schweikard, A. & Rückert, E., 18 Sept 2019, In: Current directions in biomedical engineering. 5.2019, 1, p. 145-148 4 p.Research output: Contribution to journal › Article › Research › peer-review
- 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
Intrinsic motivation and mental replay enable efficient online adaptation in stochastic recurrent networks
Tanneberg, D., Peters, J. & Rueckert, E., Jan 2019, In: Neural networks. 109.2019, January, p. 67-80 14 p.Research output: Contribution to journal › Article › Research › 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
REAL-2019: Robot open-Ended Autonomous Learning competition
Cartoni, E., Mannella, F., Santucci, V. G., Triesch, J., Rückert, E. & Baldassarre, G., 2019, Proceedings of Machine Learning Research: 3rd Annual Conference on Neural Information Processing Systems, NeurIPS 2019. Vol. 123.2019. p. 142-152 11 p. (Proceedings of Machine Learning Research).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
