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Friedemann Pulvermüller and Andreas Knoblauch , "Discrete combinatorial circuits emerging in neural networks: A mechanism for rules of grammar in the human brain?", Neural Networks, vol. 22, pp. 161–172, 2009.
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Tobias Rodemann, Frank Joublin, Christian Goerick , "Audio Proto Objects for Improved Sound Localization", IEEE-RSJ International Conference on Intelligent Robot and Systems (IROS 2009), 2009.
AbstractIn this article we present a new framework for auditory processing that combines feature extraction and grouping processes to form what we call audio proto objects. These proto objects combine an arbitrary number of audio features in a compact representation that allows a more precise sound localization and also better interfacing to behavior-control in robotics. We compare our standard sound localization system with the new approach in several s...
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Matthew Howard , "Learning Control Policies from Constrained Motion", University of Edinburgh, 2009.
AbstractMany everyday human skills can be framed in terms of performing some task subject to constraints imposed by the task or the environment. Constraints are usually unobservable and frequently change between contexts. In this thesis, we explore the problem of learning control policies from data containing variable, dynamic and non-linear constraints on motion. We show that an effective approach for doing this is to learn the unconstrained policy in a...
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Thomas H Weisswange, Constantin Rothkopf, Tobias Rodemann, Jochen Triesch , "Can reinforcement learning explain the development of causal inference in multisensory integration?", Proceedings of the IEEE 8th International Conference on Development and Learning (ICDL), 2009.
AbstractBayesian inference techniques have been used to understand the performance of human subjects on a large number of sensory tasks. Particularly, it has been shown that humans integrate sensory inputs from multiple cues in an optimal way in many conditions. Recently it has also been proposed that causal inference [1] can well describe the way humans select the most plausible model for a given input. It is still unclear how those problems are solved ...
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Matthias Rolf, Jochen Steil, Michael Gienger , "Efficient exploration and learning of whole body kinematics", Proceedings of the The 8th International Conference on Development and Learning, 2009.
AbstractWe present a neural network approach to early motor learning. The goal is to explore the needs for bootstrapping the control of hand movements in a biologically plausible learning scenario. The model is applied to the control of hand postures of the humanoid robot ASIMO by means of full upper body movements. For training, we use an efficient online scheme for recurrent reservoir networks consisting of supervised backpropagation-decorrelation outp...
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Daniel Weiler and Julian Eggert , "Level-Set Segmentation with Contour based Object Representation", Proceedings of the 2009 International Joint Conference on Neural Networks (IJCNN), 2009.
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Yaochu Jin, Honglian Guo, Yan Meng , "Robustness analysis and failure recovery of a bio-inspired self-organizing multi-robot system", Third IEEE International Conference on Self-Adaptive and Self-organizing Systems, pp. 154–164, 2009.
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Chen Zhang and Julian Eggert , "Tracking with Multiple Prediction Models", Artificial Neural Networks - ICANN, 19th International Conference, pp. 855-864, 2009.
AbstractIn Bayesian-based tracking systems, prediction is an essential part of the framework. It models object motion and links the internal estimated motion parameters with sensory measurement of the object from the outside world. In this paper a Bayesian-based tracking system with multiple prediction models is introduced. The benefit of multiple model prediction is that each of the models has individual strengths suited for different situations. For ex...
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Andre Justus , "Nutzung der Tiefeninformationen eines Lasersensors zur Erweiterung einer Fahrspuridentifikation fuer ein Fahrerassistenzsystem", Bielefeld University, 2009.
AbstractIn new vehicles, increasingly more advanced driver assistance systems (ADASs) have been incorporated in order to assist the driver in dangerous situations. Through warnings and interventions, ADASs increase the safety of the driver and others using the road. At the moment, mainly cameras and radar sensors are used in ADASs for sensing the environment. Laser sensors may also be used and present an advantage to radar in that they can detect slow mo...
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Sven Rebhan and Julian Eggert , "Consistent Modeling of Functional Dependencies along with World Knowledge", Proceedings of the International Conference on Cognitive Information Systems Engineering (ICCISE), pp. 341-348, 2009.
AbstractIn this paper we propose a method for visual systems to consistently represent functional dependencies between different visual routines along with relational short- and long-term knowledge about the world. Here the visual routines are bound to visual properties of objects stored in the memory of the system. Furthermore the functional dependencies between the visual routines are seen as a graph also belonging to the object’s structure. This graph...
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