Biblio
Found 238 results
Author Title Type [ Year
] Filters: First Letter Of Last Name is R [Clear All Filters]
.
2015. Device Mismatch in a Neuromorphic System Implements Random Features for Regression. Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE. :1–4.
.
2015. Device Mismatch in a Neuromorphic System Implements Random Features for Regression. Biomedical Circuits and Systems Conference (BioCAS), 2015 IEEE. :1–4.
.
2015. Effect of exploratory perturbation on the formation of kinematic synergies in Goal Babbling. 2015 Joint IEEE International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob).
.
2015. Efficient Policy Search in Low-dimensional Embedding Spaces by Generalizing Motion Primitives with a Parameterized Skill Memory. Autonomous Robots. 38:331–348.
.
2015. Impact of Regularization on the Model Space for Time Series Classification. New Challenges in Neural Computation (NC2). :49–56.
.
2015. A Multi-Level Control Architecture for the Bionic Handling Assistant. Advanced Robotics. 29:847–859.
.
2015. A Multi-Level Control Architecture for the Bionic Handling Assistant. Advanced Robotics. 29:847–859.
.
2015. Multiple Task Optimization with a Mixture of Controllers for Motion Generation. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). :6416–6421.
.
2015. Workspace and Pivot Point for Robot assisted Endoscope Guidance in Functional Endonasal Sinus Surgery (FESS). Int. J. of of Medical Robotics and Computer Assisted Surgery. 11:30–37.
.
2016. Continuous Task-Priority Rearrangement during Motion Execution with a Mixture of Torque Controllers. Proc. IEEE Humanoids.
.
2016. Generalizing the Inverse Dynamic Model of KUKA LWR IV+ for Load Variations using Regression in the Model Space. Proceedings of IEEE Int. Conf. Intelligent Robots and Systems. :606–611.
.
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.
.
2016. Hybrid Mechanical and Data-driven Modeling Improves Inverse Kinematic Control of a Soft Robot. Procedia Technology. 26:12–19.
.
2016. Incremental Bootstrapping of Parameterized Motor Skills. Proc. IEEE Humanoids.
.
2016. Modelling of Parameterized Processes via Regression in the Model Space. Proceedings of 24th European Symposium on Artificial Neural Networks. :53–58.
.
2016. Time Series Classification in Reservoir- and Model-Space: A Comparison. Proc. 7th IAPR Workshop on Artificial Neural Networks in Pattern Recognition.
.
2017. Hybrid Analytical and Data-driven Modeling for Feed-forward Robot Control. Sensors. 17(2)
.
2017. Learning Inverse Statics Models Efficiently. arXiv.
.
2017. Modelling of Parametrized Processes via Regression in the Model Space of Neural Networks. Neurocomputing. 268(C):55-63.
.
2017. Time Series Classification in Reservoir- and Model-Space. Neural Processing Letters. 48(3):789–809.
.
2017. Towards Grasping with Spiking Neural Networks for Anthropomorphic Robot Hands. ICANN 2017 - The 26th International Conference on Artificial Neural Networks.
.
2018. From social interaction to ethical AI: a developmental roadmap. ICDL-EPIROB 2018.
.
2018. Learning Forward and Inverse Kinematics Maps Efficiently. IROS 2018.
.
2018. Learning Inverse Statics Models Efficiently with Symmetry-Based Exploration. Frontiers in Neurorobotics.
.
2018. Maschinelles Lernen in technischen Systemen. Steigerung der Intelligenz mechatronischer Systeme. :pp.73-118.
