Elmar Rückert

Research output

  1. 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. 6.2016, 1, 12 p., 28455 / 6694.

    Research output: Contribution to journalArticleResearchpeer-review

  2. Recurrent Spiking Networks Solve Planning Tasks

    Rückert, E., Kappel, D., Tanneberg, D., Pecevski, D. & Peters, J., 18 Feb 2016, In: Scientific reports. 6.2016, 21142, 10 p., 21142.

    Research output: Contribution to journalArticleResearchpeer-review

  3. 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 journalArticleResearchpeer-review

  4. 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 journalArticleResearchpeer-review

  5. 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 proceedingChapterResearch

  6. Published

    Loop closure detection in closed environments

    Rottmann, N., Bruder, R., Schweikard, A. & Rueckert, E., Sept 2019.

    Research output: Contribution to conferencePaperpeer-review

  7. 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 conferencePaperpeer-review

  8. 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 conferencePaperpeer-review

  9. 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 proceedingConference contribution

  10. 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 journalArticleResearchpeer-review