Biblio

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Rayyes R, Kubus D, Steil JJ.  2018.  Learning Inverse Statics Models Efficiently with Symmetry-Based Exploration. Frontiers in Neurorobotics.
Weirich A, Haumann C, Steil JJ, Schüler S..  2011.  Learning Lab - Physical Interaction with Humanoid Robots for Pupils. Proc. Robotics in Education. :21–28.
Weng S, Wersing H, Steil JJ, Ritter H.  2006.  Learning Lateral Interactions for Feature Binding and Sensory Segmentation from Prototypic Basis Interactions. IEEE Trans. Neural Networks. 17:843–862.
Kober J, Gienger M, Steil JJ.  2015.  Learning Movement Primitives for Force Interaction Tasks. ICRA. :3192–3199.
Neumann K, Steil JJ.  2015.  Learning Robot Motions with Stable Dynamical Systems under Diffeomorphic Transformations. Robotics and Autonomous Systems. 70:1–15.
Malekzadeh M, Queißer J, Steil JJ.  2016.  Learning the end-effector pose from demonstration for the Bionic Handling Assistant robot.
Soltoggio A, Reinhart F, Lemme A, Steil JJ.  2013.  Learning the rules of a game: neural conditioning in human-robot interaction with delayed rewards.
Freire A, Lemme A, Steil JJ, Baretto G.  2012.  Learning visuo-motor coordination for pointing without depth calculation. Proc. European Symposium on Artificial Neural Networks. :91–96.
Reinhart F, Steil JJ.  2012.  Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.
Steil JJ, Krüger S.  2013.  Lernen und Sicherheit in Interaktion mit Robotern aus Maschinensicht. Robotik und Gesetzgebung. 2:51–71.
Steil JJ.  2000.  Local input-output stability of recurrent networks with time-varying weights. Proc. European Symposium Artificial Neural Networks. :281–286.
Steil JJ.  2002.  Local structural stability of recurrent networks with time-varying weights. Neurocomputing. 48:39–51.
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Ritter H, Haschke R, Röthling F, Steil JJ.  2011.  Manual Intelligence as a Rosetta Stone for Robot Cognition. Robotics Research. 66:135–146.
Reinhart F, Neumann K, Aswolinskiy W, Steil JJ, Hammer B.  2018.  Maschinelles Lernen in technischen Systemen. Steigerung der Intelligenz mechatronischer Systeme. :pp.73-118.
Steil JJ, Wrede S.  2019.  Maschinelles Lernen und lernende Assistenzsysteme - Neue Tätigkeiten, Rollen und Anforderungen für Beschäftigte? Berufsbildung in Wissenschaft und Praxis – BWP. 3:14-18.
Rolf M, Steil JJ, Gienger M.  2010.  Mastering Growth while Bootstrapping Sensorimotor Coordination. Int. Conf. on Epigenetic Robotics.
Steil JJ, Ritter H.  1999.  Maximisation of stability ranges for recurrent neural networks subject to on-line adaptation. Proc. European Symposium Artificial Neural Networks. :369–374.
Steil JJ.  2005.  Memory in Backpropagation-Decorrelation O(N) Efficient Online Recurrent Learning. LNCS. 3697:649–654.
Ritter H, Steil JJ, Sagerer G.  2010.  Mit Kopf, Körper und Hand: Herausforderungen Humanoider Roboter. Automatisierungstechnik, special issue on "humnoid robotics". 58:630–638.
Seidel D, Emmerich C, Steil JJ.  2014.  Model-free Path Planning for Redundant Robots using Sparse Data from Kinesthetic Teaching. Proc. of the Int. Conference on Intelligent Robots and Systems (IROS). :4381–4388.
Dehio N, Smith J, Wigand D, Xin G, Lin H-C, Steil JJ, Mistry M.  2018.  Modeling & Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics during Grasping. Int. Conf. Robotics and Automation.
Nordmann A, Wrede S, Steil JJ.  2015.  Modeling of Movement Control Architectures based on Motion Primitives using Domain-Specific Languages.
Aswolinskiy W, Reinhart F, Steil JJ.  2016.  Modelling of Parameterized Processes via Regression in the Model Space. Proceedings of 24th European Symposium on Artificial Neural Networks. :53–58.
Aswolinskiy W, Reinhart F, Steil JJ.  2017.  Modelling of Parametrized Processes via Regression in the Model Space of Neural Networks. Neurocomputing. 268(C):55-63.
Wrede S, Wojtynek M, Steil JJ, Beyer O, Frobieter C, Franke V.  2016.  Modulare Fertigungslinien für die individualisierte Produktion. Werkstattstechnik online. 4:204-210.

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