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Honglian Guo, Yan Meng, Yaochu Jin , "A Cellular Mechanism for Multi-Robot Construction via Evolutionary Multi-Objective Optimization of A Gene Regulatory Network", BioSystems, vol. 98, no. 3, pp. 193-203, 2009.
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Benjamin Dittes, Martin Heracles, Thomas Michalke, Robert Kastner, Alexander Gepperth, Jannik Fritsch, Christian Goerick , "A Hierarchical System Integration Approach with Application to Visual Scene Exploration for Driver Assistance", Proceedings of the 7th International Conference on Computer Vision Systems, Liége, Belgium, Octobre 13-15, 2009, pp. 255-264, 2009.
AbstractA scene exploration which is quick and complete according to current task is the foundation for most higher scene processing. Many specialized approaches exist in the driver assistance domain (e.g. car recognition or lane marking detection), but we aim at an integrated system, combining several such techniques to achieve sufficient performance. In this work we present a novel approach to this integration problem. Algorithms are contained in hiera...
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Ben Jones, Yaochu Jin, Bernhard Sendhoff, Xin Yao , "The Effect of Proprioceptive Feedback on the Distribution of Sensory Information in a Model of an Undulating Organism", 10th European Conference on Artificial Life, 2009.
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Manuel Mühlig, Michael Gienger, Jochen Steil, Christian Goerick , "Automatic Selection of Task Spaces for Imitation Learning", IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2009.
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Sven Hellbach, Julian Eggert, Edgar Körner, Horst-Michael Groß , "Basis Decomposition of Motion Trajectories Using Spatio-temporal NMF", Artificial Neural Networks - {ICANN} 2009, 19th International Conference, pp. 804–814, 2009.
AbstractThis paper’s intention is to present a new approach for decomposing motion trajectories. The proposed algorithm is based on nonnegative matrix factorization, which is applied to a grid like representation of the trajectories. From a set of training samples a number of basis primitives is generated. These basis primitives are applied to reconstruct an observed trajectory. Hence, the reconstruction information can be used for classification. Furthe...
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Julian Eggert, Sven Hellbach, Alexander Kolarow, Edgar Körner, Horst-Michael Groß , "Prediction and Classification of Motion Trajectories Using Spatio-Temporal NMF", {KI} 2009: Advances in Artificial Intelligence, 32nd Annual German Conference on {AI}, Paderborn, Germany, September 15-18, 2009. Proceedings, pp. 597–606, 2009.
AbstractThis paper's intention is to present a new approach for decomposing motion trajectories. The proposed algorithm is based on nonnegative matrix factorization, which is applied to a grid like representation of the trajectories. From a set of training samples a number of basis primitives is generated. These basis primitives are applied to reconstruct an observed trajectory. The reconstruction information can be used afterwards for classi cation. An ...
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Martin Heracles, Ursula Körner, Thomas Michalke, Gerhard Sagerer, Jannik Fritsch, Christian Goerick , "A Dynamic Attention System that Reorients to Unexpected Motion in Real-World Traffic Environments", International Conference on Intelligent Robots and Systems (IROS), 2009.
AbstractIn this paper we propose a system architecture that extends the current state-of-the-art in computational visual attention by incorporating the biological concept of ventral attention. According to recent findings regarding the neurobiological foundations of attention, there exist two separate but interacting attention systems in the human brain: the dorsal attention system and the ventral attention system. As opposed to the well-known computatio...
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Matthew Howard, Stefan Klanke, Michael Gienger, Christian Goerick, Sethu Vijayakumar , "Behaviour Generation in Humanoids by Learning Potential-based Policies from Constrained Motion", Applied Bionics and Biomechanics, vol. - Special Issue on Humanoid Robots, 2009.
AbstractMovement generation that is consistent with observed or demonstrated behaviour is an efficient way to seed movement planning in complex, high dimensional movement systems like humanoid robots. We present a method for learning potential-based policies from constrained motion data. In contrast to previous approaches to direct policy learning, our method can combine observations from a variety of contexts where different constraints are in force, to...
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Stephan Hasler, Heiko Wersing, Stephan Kirstein, Edgar Körner , "Large-Scale Real-Time Object Identification Based on Analytic Features", Artificial Neural Networks – ICANN 2009, pp. 663–672, 2009.
AbstractInspired by biological findings, we present a system that is able to robustly identify a large number of pre-trained objects in real-time. In contrast to related work, we do not restrict the objects' pose to characteristic views but rotate them freely in hand in front of a cluttered background. We describe the essential system's ingredients, like prototype-based figure-ground segmentation, extraction of brain-like analytic features, and a simple ...
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Anna-Lisa Vollmer, Kathrin Lohan, Kerstin Fischer, Yukie Nagai, Karola Pitsch, Jannik Fritsch, Katharina Rohlfing, Britta Wrede , "People Modify Their Tutoring Behavior in Robot-Directed Interaction for Action Learning", International Conference on Development and Learning, 2009.
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