Biblio
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2012. Goal Babbling: a New Concept for Early Sensorimotor Exploration. Proceedings of Workshop on Developmental Robotics.
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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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2009. Goal-directed movement generation with a transient-based recurrent neural network controller. Advanced Technologies for Enhanced Quality of Life. :112–117.
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2001. Guiding Attention for Grasping Tasks by Gestural Instruction: The GRAVIS-Robot Architecture. Proc. Int. Conf. Intelligent Robots and Sytems. :1570–1577.
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2020. Hierarchical Interest-Driven Goal Babbling for Efficient Bootstrapping of Sensorimotor skills. ICRA .
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2010. Human-Robot Interaction for Learning and Adaptation of Object Movements. IEEE Int. Conf. Intelligent Robots and Systems. :4901–4907.
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2016. Hybrid Mechanical and Data-driven Modeling Improves Inverse Kinematic Control of a Soft Robot. Procedia Technology. 26:12–19.
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2010. Imitating object movement skills with robots — A task-level approach exploiting generalization and invariance. The IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems : Conference Proceedings. :1262–1269.
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2017. Imitation learning for a continuum trunk robot. Proceedings of the 25. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.
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2015. Impact of Regularization on the Model Space for Time Series Classification. New Challenges in Neural Computation (NC2). :49–56.
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2016. Improving the Inverse Dynamics Model of the KUKA LWR IV+ using Independent Joint Learning. Proceedings 7th IFAC Symposium on Mechatronic Systems. :507––512.
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2016. Incremental Bootstrapping of Parameterized Motor Skills. Proc. IEEE Humanoids.
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2009. Incremental Figure-Ground Segmentation using localized adaptive metrics in LVQ. International Workshop on Self-Organizing Maps (WSOM). :45–53.
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2015. Independent Joint Learning in Practice: Local Error Estimates to Improve Inverse Dynamics Control. :643–650.
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2004. Input Space Bifurcation Manifolds of RNNs. Proc. European Symposium Artificial Neural Networks. :13–19.
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1998. Input-Output Stability of Recurrent Neural Networks with Delays using Circle Criteria. Proc. Int. ICSC/IFAC Symposium on Neural Computation. :519–525.
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2009. Integrating Inhomogeneous Processing and Proto-object Formation in a Computational Model of Visual Attention. Human Centered Robot Systems: Cognition, Interaction, Technology. :93–102.
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2010. Interactive Learning of Inverse Kinematics with Nullspace Constraints using Recurrent Neural Networks. Proc. 20. Workshop on Computational Intelligence.
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2012. Intrinsic Plasticity via Natural Gradient Decent. 20th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012). Proceedings. :555–560.
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1997. A Layered Recurrent Neural Network for Feature Grouping. Int. Conf. on Artificial Neural Networks. :439–444.
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2003. Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.
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2010. Learning Flexible Full Body Kinematics for Humanoid Tool Use. Int. Symp. Learning and Adaptive Behavior in Robotic Systems (Best Paper Award). :171–176.
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2018. Learning Forward and Inverse Kinematics Maps Efficiently. IROS 2018.
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2010. Learning Inverse Kinematics for Pose-Constraint Bi-Manual Movements. From Animals to Animats 11. 11th International Conference on Simulation of Adaptive Behavior, SAB 2010. Proceedings. 6226
