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Transferring Experience from Simulation to the Real World for Precise Pick-And-Place Tasks in Highly Cluttered Scenes

K. Kleeberger, M. Völk, M. Moosmann, E. Thiessenhusen, F. Roth, R. Bormann, and M. Huber. 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), page 9681-9688. Piscataway, IEEE, (2020)
DOI: 10.1109/IROS45743.2020.9341709

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Univ. -Prof. Dr. -Ing. habil. Marco Huber University of Stuttgart

F. Dörr

Marco Ströbel University of Stuttgart

F. Laufer

F. Rusitschka

Other publications of authors with the same name

Recursive Gaussian process: On-line regression and learning.M. Huber. Pattern Recognition Letters, (2014)Parameter identification and reconstruction for distributed phenomena based on hybrid density filter.F. Sawo, M. Huber, and U. Hanebeck. FUSION, page 1-8. IEEE, (2007)Instantaneous pose estimation using rotation vectors.F. Beutler, M. Huber, and U. Hanebeck. ICASSP, page 3413-3416. IEEE, (2009)Survey on Automated Machine Learning.M. Zöller, and M. Huber. CoRR, (2019)Stochastic model predictive control of time-variant nonlinear systems with imperfect state information.F. Weissel, T. Schreiter, M. Huber, and U. Hanebeck. MFI, page 40-46. IEEE, (2008)On entropy approximation for Gaussian mixture random vectors.M. Huber, T. Bailey, H. Durrant-Whyte, and U. Hanebeck. MFI, page 181-188. IEEE, (2008)Semi-analytic stochastic linearization for range-based pose tracking.F. Beutler, M. Huber, and U. Hanebeck. MFI, page 44-49. IEEE, (2010)Closed-Form Prediction of Nonlinear Dynamic Systems by Means of Gaussian Mixture Approximation of the Transition Density.M. Huber, D. Brunn, and U. Hanebeck. MFI, page 98-103. IEEE, (2006)Hybrid transition density approximation for efficient recursive prediction of nonlinear dynamic systems.M. Huber, and U. Hanebeck. IPSN, page 283-292. ACM, (2007)Reduced Feature Set for Emotion Recognition Based on Angle and Size Information.P. Dunau, M. Bonny, M. Huber, and J. Beyerer. IAS, volume 867 of Advances in Intelligent Systems and Computing, page 585-596. Springer, (2018)