Biblio
Situated robot learning for multi-modal instruction and imitation of grasping. Robotics and Autonomous Systems. 47:129–141.
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2004. Robust control in closed loops realised by fast signal transmission of infinite gain neurons. Proc. Int. Conf. Artificial Neural Networks. 1:260–266.
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2000. What do humanoid robots offer to experimental psychology ? Connectionist models of neurocognition and emergent behavior : from theory to applications ; proceedings of the 12th Neural Computation and Psychology Workshop, Birkbeck, University of London, 8 - 10 April 2010. 20:361–371.
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2011. Unsupervised Clustering of Continuous Trajectories of Kinematic Trees with SOM-SD. Proc. European Symposium on Artificial Neural Networks.
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2006. .
1999. .
2019. .
1999.
Full 6-DOF Admittance Control for the Industrial Robot Stäubli TX60. 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE). :1450-1455.
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2019. Full 6-DOF Admittance Control for the Industrial Robot Stäubli TX60. International Conference on Automation Science and Engineering (CASE).
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2019. Towards Grasping with Spiking Neural Networks for Anthropomorphic Robot Hands. ICANN 2017 - The 26th International Conference on Artificial Neural Networks.
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2017. .
2014. Learning Lab - Physical Interaction with Humanoid Robots for Pupils. Proc. Robotics in Education. :21–28.
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2011. teutolab-robotik - Hands-On Teaching of Human-Robot Interaction. Proc. Int. Conf. on SIMULATION, MODELING and PROGRAMMING for AUTONOMOUS ROBOTS, Workshop on "Teaching Robotics-Teaching with Robotics". :474–483.
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2010. Learning Compatibitlity Functions for Feature Binding and Perceptual Grouping. Proc. of Int. Conference Artificial Neural Networks. LNCS 2714:60–67.
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2003. Learning Lateral Interactions for Feature Binding and Sensory Segmentation from Prototypic Basis Interactions. IEEE Trans. Neural Networks. 17:843–862.
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2006. Data Driven Generation of Interactions for Feature Bindingand Relaxation Labeling. Proc. Int. Conf. Artificial Neural Networks. :432–437.
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2002. Online Learning of Objects and Faces in an Integrated Biologically Motivated Architecture. International Conference on Computer Vision Systems.
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2007. A Competitive Layer Model for Feature Binding and Sensory Segmentation. Neural Computation. 13:357–387.
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2001. Online Learning of Objects in a Biologically Motivated Visual Architecture. International Journal of Neural Systems. 17:219–230.
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2007. A Layered Recurrent Neural Network for Feature Grouping. Int. Conf. on Artificial Neural Networks. :439–444.
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1997. .
2009. A biologically motivated system for unconstrained online learning of visual objects. Proc. of the Int. Conf. on Artificial Neural Networks (ICANN). 2:508–517.
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2006. An Open-Source Architecture for Simulation, Execution and Analysis of Real-Time Robotics Systems. SIMPAR.
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2018. 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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2009. Where to Look Next? Combining Static and Dynamic Proto-objects in a TVA-based Model of Visual Attention Cognitive Computation. 2:326–343.
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2010.