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Tobias Rodemann, Kalina Karova, Frank Joublin, Christian Goerick, "Purely Auditory Online-Adaptation of Auditory-Motor Maps", IEEE-RSJ International Conference on Intelligent Robot and Systems (IROS 2007), 2007.

Abstract

We present a system for an online-adaptation of auditory-motor maps that doesn't require a special set-up or dedicated robot movements and can therefore work during the normal operation of the robot. Our approach is based purely on auditory cues and motor position feedback for estimating the correct sound source position. The system can learn the correct auditory-motor map within 1–2 hours, starting from a random initialization, in a room with ...



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Yaochu Jin, Bernhard Sendhoff, Edgar Körner, "Rule extraction from compact Pareto-optimal neural networks", Multi-objective Evolutionary Algorithms for Knowledge from Databases, Springer, 2007.



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Mark Toussaint, Michael Gienger, Christian Goerick, "Optimization of Sequential Attractor-based Movement for Compact Behaviour Generation", IEEE-RAS International Conference on Humanoid Robots, 2007.

Abstract

In this paper, we propose a novel method to generate optimal robot motion based on a sequence of attractor dynamics in task space. This is motivated by the biological evidence that movements in the motor cortex of animals are encoded in a similar fashion – and by the need for compact movement representations on which efficient optimization can be performed. We represent the motion as a sequence of attractor points acting in the task space of th...



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Christian Goerick, Bram Bolder, Herbert Janßen, Michael Gienger, Hisashi Sugiura, Mark Dunn, Inna Mikhailova, Tobias Rodemann, Heiko Wersing, Stephan Kirstein, "Towards Incremental Hierarchical Behavior Generation for Humanoids", IEEE-RAS International Conference on Humanoids 2007, 2007.

Abstract

The contribution of this paper is twofold. First, we present a new conceptual framework for modeling incremental hierarchical behavior control systems for humanoids. The biological motivation and the key elements are discussed. Second, we show our current instance of such a behavior control system, called ALIS. It is designed according to the concepts presented within the framework. The system is integrated with the humanoid ASIMO and comprises v...



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Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, "A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation", Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), pp. 1288–1295, 2007.



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Rüdiger Kupper, Andreas Knoblauch, Ursula Körner, Edgar Körner, Marc-Oliver Gewaltig, "Recollection and imagination in a functional model of visual cortex", Proceedings of the Computational Neuroscience Conference (CNS), pp. S10, 2007.

Abstract

In Kupper et al., Neurocomp. 70(10-12), 1711-1716 (2007), we have presented a model of signal flow in functional cortical columns, across the six cortical layers and between several cortical areas. We showed how the columnar subsystems interact to predict and recognize stimuli in terms of locally stored knowledge. In this model, columnar communication integrated bottom-up signals with internally generated top-down signals to describe the stimulus...



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Andreas Knoblauch, Friedrich Sommer, Marc-Oliver Gewaltig, Rüdiger Kupper, Ursula Körner, Edgar Körner, "A model for structural plasticity in neocortical associative networks trained by the hippocampus.", BMC Neuroscience, vol. 8(Suppl 2), pp. S14, 2007.



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Alexander Gepperth, Britta Mersch, Christian Goerick, Jannik Fritsch, "Color object recognition in real-world scenes", Artificial Neural Networks, 17th International Conference ICANN, Part II, Springer Verlag, pp. 583-592, 2007.

Abstract

This work investigates the role of color in object recognition. We approach the problem from a computational perspective by measuring the performance of biologically inspired object recognition methods. As benchmarks, we use image datasets proceeding from a real-world object detection scenario and compare classification performance using color and gray-scale versions of the same datasets. In order to make our results as general as possible, we co...



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Volker Willert, Mark Toussaint, Julian Eggert, Edgar Körner, "Uncertainty Optimization for Robust Dynamic Optical Flow Estimation", Proceedings of the 2007 International Conference on Machine Learning and Applications (ICMLA), 2007.

Abstract

We develop an optical flow estimation framework that focuses on motion estimation over time formulated in a Dynamic Bayesian Network. It realizes a spatiotemporal integration of motion information using a dynamic and robust prior that incorporates spatial and temporal coherence constraints on the flow field. The main contribution is the embedding of these particular assumptions on optical flow evolution into the Bayesian propagation approach that...



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Michael Gienger, Bram Bolder, Mark Dunn, Hisashi Sugiura, Herbert Janßen, Christian Goerick, "Predictive behaviour generation - A sensor-based walking and reaching architecture for humanoid robots", Autonome Mobile Systeme 2007, issue siebte, pp. 275-281, 2007.

Abstract

This contribution presents a sensor-based walking and reaching architecture for humanoid robots. It enables a humanoid robot to interact with its environment using a smooth whole body motion control driven by stabilized visual targets. Interactive selection mechanisms are used to switch between behavior alternatives for searching or tracking objects as well as different whole body motion strategies for reaching. The decision between different mot...



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