Biblio

Found 232 results
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Filters: Author is Jochen J. Steil  [Clear All Filters]
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Kubus D, Rayyes R, Steil JJ.  2018.  Learning Forward and Inverse Kinematics Maps Efficiently. IROS 2018.
Rolf M, Steil JJ, Gienger M.  2010.  Learning Flexible Full Body Kinematics for Humanoid Tool Use. Int. Symp. Learning and Adaptive Behavior in Robotic Systems (Best Paper Award). :171–176.
Weng S., Steil JJ.  2003.  Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.
Wersing H, Steil JJ, Ritter H.  1997.  A Layered Recurrent Neural Network for Feature Grouping. Int. Conf. on Artificial Neural Networks. :439–444.
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Huchler N, Adolph L, André E, Bauer W, Bender N, Müller N, Neuburger R, Peissner M, Steil JJ, Stowasser S et al..  2020.  Kriterien für die menschengerechte Gestaltung der Mensch-Maschine-Interaktion bei Lernenden Systemen – Whitepaper aus der Plattform Lernende Systeme.
Steil JJ.  2021.  "Können Maschinen Ethisches Verhalten Lernen ?" Bericht zum 1. SYnENZ Zirkel der BWG Kommission für Synergie und Intelligenz (SYnENZ) Jahrbuch der Braunschweigischen Wissenschaftlichen Gesellschaft. :117-120.
Steil JJ, Maier GW.  2020.  Kollaborative Roboter – universale Werkzeuge in der digitalisierten und vernetzten Arbeitswelt. G. W. Maier, G. Engels, E. Steffen (Hrg.): Handbuch Gestaltung digitaler und vernetzter Arbeitswelten. :323-346.
Steil JJ, Emmerich C, Swadzba A, Grünberg R, Nordmann A, Wrede S.  2013.  Kinesthetic Teaching Using Assisted Gravity Compensation for Model-Free Trajectory Generation in Confined Spaces. Gearing Up and Accelerating Cross-Fertilization between Academic and Industrial Robotics Research in Europe. 94:107–127.
Lemme A, Freire A, Barreto G, Steil JJ.  2013.  Kinesthetic teaching of visuomotor coordination for pointing by the humanoid robot iCub. Neurocomputing. 112:179–188.
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Neumann K, Strub C, Steil JJ.  2013.  Intrinsic Plasticity via Natural Gradient Descent with Application to Drift Compensation. Neurocomputing. 112:26–33.
Neumann K, Steil JJ.  2012.  Intrinsic Plasticity via Natural Gradient Decent. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). Proceedings. :555–560.
Rayyes R, Donat H, Steil JJ, Spranger M.  2021.  Interest-Driven Exploration with Observational Learning for Developmental Robots. IEEE Transactions on Cognitive and Developmental Systems .
Rayyes R, Donat H, Steil JJ.  2021.  Interest-Driven Exploration for Real Robot Applications: Sample-Efficiency, High-Accuracy, and Robustness.
Emmerich C, Nordmann A, Swadzba A, Wrede S, Steil JJ.  2012.  Interactive Learning of Inverse Kinematics with Null-space Constraints using Recurrent Neural Networks.
Wrede S, Johannfunke M, Lemme A, Nordmann A, Rüther S, Weirich A, Steil JJ.  2010.  Interactive Learning of Inverse Kinematics with Nullspace Constraints using Recurrent Neural Networks. Proc. 20. Workshop on Computational Intelligence.
Muehlig M, Steil JJ, Gienger M..  2012.  Interactive Imitation Learning of Object Movement Skills. Autonomous Robots. 32:97–114.
Steil JJ, Wrede S.  2012.  Intelligent Interfaces between Humans and Technology. 22:2.
Wischnewski M, Steil JJ, Kehrer L, Schneider WX.  2009.  Integrating Inhomogeneous Processing and Proto-object Formation in a Computational Model of Visual Attention. Human Centered Robot Systems: Cognition, Interaction, Technology. :93–102.
Steffen JFrederik, Pardowitz M, Steil JJ, Ritter H.  2011.  Integrating Feature Maps and Competitive Layer Architectures For Motion Segmentation. Neurocomputing. 74:1372–1381.
Steil JJ, Ritter H.  1998.  Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Proc. Int. ICSC/IFAC Symposium on Neural Computation. :519–525.
Steil JJ.  1999.  Input-Output Stability of Recurrent Neural Networks.
Haschke R, Steil JJ.  2004.  Input Space Bifurcation Manifolds of RNNs. Proc. European Symposium Artificial Neural Networks. :13–19.
Haschke R, Steil JJ.  2005.  Input Space Bifurcation Manifolds of Recurrent Neural Networks. Neurocomputing. 64:25–38.
Caluwaerts K, Steil JJ.  2015.  Independent Joint Learning in Practice: Local Error Estimates to Improve Inverse Dynamics Control. :643–650.
Denecke A, Wersing H, Steil JJ, Körner E.  2009.  Incremental Figure-Ground Segmentation using localized adaptive metrics in LVQ. International Workshop on Self-Organizing Maps (WSOM). :45–53.

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