Biblio
Found 84 results
[ Author
] Title Type Year Filters: First Letter Of Last Name is R [Clear All Filters]
.
2019. Goal-Related Feedback Guides Motor Exploration and Redundancy Resolution in Human Motor Skill Acquisition. PLOS Computational Biology. 15(3):1-27.
.
2006. Distributed Sensing and Prediction of Obstacle Motions for Mobile Robot Motion Planning. IEEE International Conference on Intelligent Robots and Systems. :4833–4838.
.
2003. Analyse und Kompensation von Fahrfehlern bei Mecanum-Wheel-Fahrzeugen. Autonome Mobile Systeme 2003, 19. Fachgespräch, Karlsruhe. :75–82.
.
2005. Graphbasierte Bewegungsanalyse dynamischer Hindernisse zur Steuerung mobiler Roboter. Autonome Mobile Systeme 2005, 20. Fachgespräch Stuttgart. :295–301.
.
2009. Attractor-based computation with reservoirs for online learning of inverse kinematics. European Symposium Artificial Neural Networks (ESANN). :257–262.
.
2011. A constrained regularization approach for input-driven recurrent neural networks. Differential Equations and Dynamical Systems. 19:27–46.
.
2010. Tacking reduces bow-diving of high-speed unmanned sea surface vehicles. Int. Symp. Learning and Adaptive Behavior in Robotic Systems. :177–182.
.
2015. Efficient Policy Search in Low-dimensional Embedding Spaces by Generalizing Motion Primitives with a Parameterized Skill Memory. Autonomous Robots. 38:331–348.
.
2012. Representation and Generalization of Bi-manual Skills from Kinesthetic Teaching. IEEE-RAS International Conference on Humanoid Robots. :560–567.
.
2011. Neural learning and dynamical selection of redundant solutions for inverse kinematic control. Proc. IEEE Int. Conf. Humanoid Robots. :564–569.
.
2017. Hybrid Analytical and Data-driven Modeling for Feed-forward Robot Control. Sensors. 17(2)
.
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.
.
2011. Reservoir regularization stabilizes learning of Echo State Networks with output feedback. Proc. European Symposium on Artificial Neural Networks. :59–64.
.
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.
.
2014. Efficient Policy Search with a Parameterized Skill Memory. :1400–1407.
.
2009. Goal-directed movement generation with a transient-based recurrent neural network controller. Advanced Technologies for Enhanced Quality of Life. :112–117.
.
2012. Regularization and stability in reservoir networks with output feedback. Neurocomputing. 90:96–105.
.
2016. Hybrid Mechanical and Data-driven Modeling Improves Inverse Kinematic Control of a Soft Robot. Procedia Technology. 26:12–19.
.
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.
.
2012. Learning Whole Upper Body Control with Dynamic Redundancy Resolution in Coupled Associative Radial Basis Function Networks. IROS. :1487–1492.
.
2018. Maschinelles Lernen in technischen Systemen. Steigerung der Intelligenz mechatronischer Systeme. :pp.73-118.
.
2019. An architecture for AutomationML-based constraint modelling and orchestration of Incremental Manufacturing. 7th CIRP Global Web Conference.
.
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.
.
2017. Learning Inverse Statics Models Efficiently. arXiv.
