Biblio

Found 255 results
[ Author(Asc)] Title Type Year
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R
Ritter H, Steil JJ, Sagerer G.  2010.  Mit Kopf, Körper und Hand: Herausforderungen Humanoider Roboter. Automatisierungstechnik, special issue on "humnoid robotics". 58:630–638.
Richter O, Reinhart F, Nease S, Steil JJ, Chicca E.  2015.  Device Mismatch in a Neuromorphic System Implements Random Features for Regression. Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE. :1–4.
Rhode M, Narioka K, Stein L, Steil JJ, Ernst M.  2019.  Goal-Related Feedback Guides Motor Exploration and Redundancy Resolution in Human Motor Skill Acquisition. PLOS Computational Biology. 15(3):1-27.
Reinhart F, Steil JJ.  2011.  Reservoir regularization stabilizes learning of Echo State Networks with output feedback. Proc. European Symposium on Artificial Neural Networks. :59–64.
Reinhart F, Shareef Z, Steil JJ.  2017.  Hybrid Analytical and Data-driven Modeling for Feed-forward Robot Control. Sensors. 17(2)
Reinhart F, Steil JJ.  2014.  Efficient Policy Search with a Parameterized Skill Memory. :1400–1407.
Reinhart F, Steil JJ.  2009.  Reaching movement generation with a recurrent neural network based on learning inverse kinematics for the humanoid robot iCub. IEEE Conf. Humanoid Robotics. :323–330.
Reinhart F, Steil JJ.  2011.  State prediction: a constructive method to program recurrent neural networks. Artificial Neural Networks and Machine Learning – ICANN 2011 : 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. 6791:159–166.
Reinhart F, Steil JJ, Huntsberger TL, Stoica A.  2010.  Tacking reduces bow-diving of high-speed unmanned sea surface vehicles. Int. Symp. Learning and Adaptive Behavior in Robotic Systems. :177–182.
Reinhart F, Neumann K, Aswolinskiy W, Steil JJ, Hammer B.  2018.  Maschinelles Lernen in technischen Systemen. Steigerung der Intelligenz mechatronischer Systeme. :pp.73-118.
Reinhart F, Lemme A, Steil JJ.  2012.  Representation and Generalization of Bi-manual Skills from Kinesthetic Teaching. IEEE-RAS International Conference on Humanoid Robots. :560–567.
Reinhart F, Steil JJ.  2016.  Hybrid Mechanical and Data-driven Modeling Improves Inverse Kinematic Control of a Soft Robot. Procedia Technology. 26:12–19.
Reinhart F, Steil JJ.  2009.  Attractor-based computation with reservoirs for online learning of inverse kinematics. European Symposium Artificial Neural Networks (ESANN). :257–262.
Reinhart F, Steil JJ.  2011.  A constrained regularization approach for input-driven recurrent neural networks. Differential Equations and Dynamical Systems. 19:27–46.
Reinhart F, Steil JJ.  2012.  Regularization and stability in reservoir networks with output feedback. Neurocomputing. 90:96–105.
Reinhart F, Steil JJ.  2009.  Goal-directed movement generation with a transient-based recurrent neural network controller. Advanced Technologies for Enhanced Quality of Life. :112–117.
Reinhart F, Steil JJ.  2011.  Neural learning and dynamical selection of redundant solutions for inverse kinematic control. Proc. IEEE Int. Conf. Humanoid Robots. :564–569.
Reinhart F, Steil JJ.  2015.  Efficient Policy Search in Low-dimensional Embedding Spaces by Generalizing Motion Primitives with a Parameterized Skill Memory. Autonomous Robots. 38:331–348.
Reinhart F, Steil JJ.  2008.  Recurrent neural associative learning of forward and inverse kinematics for movement generation of the redundant PA-10 robot. Int. Symp. Learning Adaptive Behavior in Robotic Systems, best paper award. 1:35–40.
Reinhart F, Steil JJ.  2012.  Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.
Reichler A-K, Gabriel F, Timmann F, Steil JJ, Dröder K.  2019.  An architecture for AutomationML-based constraint modelling and orchestration of Incremental Manufacturing. 7th CIRP Global Web Conference.
Rayyes R, Steil JJ.  2019.  Online Associative Multi-Stage Goal Babbling Toward Versatile Learning of Sensorimotor Skills. Int. Conference Developmental Learning. :327-334.
Rayyes R, Kubus D, Hartmann C, Steil JJ.  2017.  Learning Inverse Statics Models Efficiently. arXiv.
Rayyes R, Kubus D, Steil JJ.  2018.  Learning Inverse Statics Models Efficiently with Symmetry-Based Exploration. Frontiers in Neurorobotics.
Rayyes R, Steil JJ.  2016.  Goal Babbling with direction sampling for simultaneous exploration and learning of inverse kinematics of a humanoid robot. Proceedings of the workshop on New Challenges in Neural Computation. 4:56–63.

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