Jens Schmüdderich,
"Multimodal learning of grounded concepts in embodied systems",
Bielefeld University, 2010.
Abstract
The research of methods equipping a technical system with the ability to learn mental concepts of objects, properties, or actions is an important step towards the understanding of intelligence. Moreover, for everyday interaction, a system acquiring knowledge by learning is obviously advantageous compared to a system that requires programming. A special challenge arises from the variety of different characteristics whose association forms our unde...
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Maha Salem, Stefan Kopp, Ipke Wachsmuth, Frank Joublin,
"Generating Multi-Modal Robot Behavior Based on a Virtual Agent Framework",
IEEE Int. Conf. on Robotics and Automation (ICAIR/ICRA), 2010.
Abstract
One of the crucial steps in the attempt to build sociable, communicative humanoid robots is to endow them with expressive non-verbal behaviors along with speech. One such behavior is gesture, frequently used by human speakers to emphasize, supplement, or even complement what they express in speech. The generation of speech-accompanying robot gesture together with an evaluation of the effects of this multi-modal behavior is still largely unexplore...
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Honglian Guo, Yan Meng, Yaochu Jin,
"Analysis of Local Communication Load in Shape Formation of a Distributed Morphogenetic Swarm Robotic System",
IEEE World Congress on Computational Intelligence, 2010.
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Matthias Rolf, Jochen Steil, Michael Gienger,
"Mastering Growth while Bootstrapping Sensorimotor Coordination",
Int. Conf. on Epigenetic Robotics (EpiRob), 2010.
Abstract
The bodily change in infancy due to growth is a fundamental challenge for the bootstrapping of sensorimotor coordination. We argue that learning by doing, and thus a babbling of goals instead of motor commands provides an appealing explanation for the success of infants in that bootstrapping. We show that Goal Babbling allows to bootstrap reaching skills during di erent growth patterns on a robot arm with ve degrees of freedom and on the infant l...
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Gökhan Ince, Kazuhiro Nakadai, Tobias Rodemann, Hiroshi Tsujino, Jun-ichi Imura,
"A Robust Speech Recognition System against the Ego Noise of a Robot",
Proceedings of Interspeech, 2010.
Abstract
This paper presents a speech recognition system for a mobile robot that attains a high recognition performance, even if the robot generates ego-motion noise. We investigate noise sup- pression and speech enhancement methods that are based on prediction of ego-motion and its noise. The estimation of ego- motion is used for superimposing white noise in a selective manner based on the ego-motion type. Moreover, instantaneous prediction of ego-motion...
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Martin Heracles, Fernando Martinelli, Jannik Fritsch,
"Vision-Based Behavior Prediction in Urban Traffic Environments by Scene Categorization",
British Machine Vision Conference (BMVC), 2010.
Abstract
We propose a method for vision-based scene understanding in urban traffic environments that predicts the appropriate behavior of a human driver in a given visual scene. The method relies on a decomposition of the visual scene into its constituent objects by image segmentation and uses segmentation-based features that represent both their identity and spatial properties. We show how the behavior prediction can be naturally formulated as scene cate...
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Miranda Grahl, Frank Joublin, Franz Kummert,
"A controlling strategy for an active vision system based on auditory and visual cues",
Int. Conf. on Artificial Neural Networks (ICANN), 2010.
Abstract
It is still an open question how preliminary visual reflexes can be structured by auditory and visual modalities in order to recognize objects. Therefore, we propose a new method for a controlling strategy for an active vision system that learns to focus on relevant multi-modal aspects of the environment. The method is bootstrapped by a bottom up visual saliency process in order to extract important visual points. In this paper, we present our re...
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Jens Schmüdderich, Nils Einecke, Stephan Hasler, Alexander Gepperth, Bram Bolder, Robert Kastner, Mathias Franzius, Sven Rebhan, Benjamin Dittes, Heiko Wersing, Julian Eggert, Jannik Fritsch, Christian Goerick,
"System Approach for Multi-Purpose Representations of Traffic Scene Elements",
IEEE 13th Int. Conf. ITSC, pp. 1677-1684, 2010.
Abstract
A major step towards intelligent vehicles lies in the acquisition of an environmental representation of sufficient generality to serve as the basis for a multitude of different assistance-relevant tasks. This acquisition process must reliably cope with the variety of environmental changes inherent to traffic environments. As a step towards this goal, we present our most recent integrated system performing object detection in challenging environme...
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Christian Goerick and Edgar Körner,
"Cognitive Humanoid Robotics: Steps toward Learning and Behavior Organization",
Automatisierungstechnik, pp. 639–646, 2010.
Abstract
In diesem Beitrag geben wir einen Überblick über unsere Forschungsarbeiten auf dem Gebiet der humanoiden Robotik mit dem Schwerpunkt auf kognitiven Systemen. Insbesondere betrachten wir eine Serie von Systemen, die wir gemäß unseres hierarchischen inkrementellen Systemansatzes erforscht, realisiert und analysiert haben....
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Michael Gienger, Manuel Mühlig, Jochen Steil,
"Imitating Object Movement Skills with Robots – A Task-Level Approach Exploiting Generalization and Invariance",
Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS), 2010.
Abstract
This paper presents an architecture for learning and reproducing movements with a robot in interaction with a human teacher. We focus on the movement representation and propose three enhancements to increase generalization capabilities: Firstly, we introduce a flexible task-level movement representation that is based on neuropsychological findings. Movement is represented in task-oriented frames of reference, and generalizes to a variety of diffe...
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