Hybrid Mechanical and Data-driven Modeling Improves Inverse Kinematic Control of a Soft Robot. Procedia Technology. 26:12–19.. 2016.
Improving the Inverse Dynamics Model of the KUKA LWR IV+ using Independent Joint Learning. Proceedings 7th IFAC Symposium on Mechatronic Systems. :507––512.. 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.
Modulare Fertigungslinien für die individualisierte Produktion. Werkstattstechnik online.. 2016.
Parameterized Pattern Generation via Regression in the Model Space of Echo State Networks. Proceedings of the Workshop on New Challenges in Neural Computation.. 2016.
Time Series Classification in Reservoir- and Model-Space: A Comparison. Proc. 7th IAPR Workshop on Artificial Neural Networks in Pattern Recognition.. 2016.
Trajectory Optimization of COmpliant HuMANoid (COMAN) Robot Arm using Path Parameter based Dynamic Programming. Proc. IEEE Humanoids. :705–710.. 2016.
Vertical Integration and Service Orchestration for Modular Production Systems using Business Process Models. Procedia Technologica. 26:259–266.. 2016.
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.
A flat neural network architecture to represent movement primitives with integrated sequencing. :481–486.. 2015.
Impact of Regularization on the Model Space for Time Series Classification. New Challenges in Neural Computation (NC2). :49–56.. 2015.
Independent Joint Learning in Practice: Local Error Estimates to Improve Inverse Dynamics Control. :643–650.. 2015.
Learning Movement Primitives for Force Interaction Tasks. ICRA. :3192–3199.. 2015.
Learning Robot Motions with Stable Dynamical Systems under Diffeomorphic Transformations. Robotics and Autonomous Systems. 70:1–15.. 2015.
Modeling of Movement Control Architectures based on Motion Primitives using Domain-Specific Languages.. 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.
Open-source benchmarking for learned reaching motion generation in robotics. Paladyn, Journal of Behavioral Robotics. 6:30–41.. 2015.