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  1. Article

    Open Access

    Modularity in Nervous Systems—a Key to Efficient Adaptivity for Deep Reinforcement Learning

    Modularity as observed in biological systems has proven valuable for guiding classical motor theories towards good answers about action selection and execution. New challenges arise when we turn to learning: T...

    Malte Schilling, Barbara Hammer, Frank W. Ohl, Helge J. Ritter… in Cognitive Computation (2023)

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    Chapter and Conference Paper

    From Geometries to Contact Graphs

    When a robot perceives its environment, it is not only important to know what kind of objects are present in it, but also how they relate to each other. For example in a cleanup task in a cluttered environment...

    Martin Meier, Robert Haschke… in Artificial Neural Networks and Machine Lea… (2020)

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    Article

    “KogniChef”: A Cognitive Cooking Assistant

    Cooking is a complex activity of daily living that requires intuition, coordination, multitasking and time-critical planning abilities. We introduce KogniChef, a cognitive cooking assistive system that provides u...

    Alexander Neumann, Christof Elbrechter… in KI - Künstliche Intelligenz (2017)

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    Chapter and Conference Paper

    Tactile Convolutional Networks for Online Slip and Rotation Detection

    We present a deep convolutional neural network which is capable to distinguish between different contact states in robotic manipulation tasks. By integrating spatial and temporal tactile sensor data from a pie...

    Martin Meier, Florian Patzelt… in Artificial Neural Networks and Machine Lea… (2016)

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    Chapter and Conference Paper

    Learning Gestalt Formations for Oscillator Networks

    The binding of similar objects to a common group is an effortless task for humans.We know if things belong together or not by intuitively relying on a set of rules. In the area of visual perception, these rule...

    Martin Meier, Robert Haschke, Helge J. Ritter in Artificial Neural Networks (2015)

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    Chapter and Conference Paper

    Learning of Lateral Interactions for Perceptual Grou** Employing Information Gain

    Perceptual Grou** is an important aspect in the understanding of sensory input. One of the major problems there is, how features can form meaningful groups while segregating from non relevant informations. O...

    Martin Meier, Robert Haschke… in Artificial Neural Networks and Machine Lea… (2013)

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    Article

    Self-Organizing Feature Maps for Modeling and Control of Robotic Manipulators

    This paper presents a review of self-organizing feature maps (SOFMs), in particular, those based on the Kohonen algorithm, applied to adaptive modeling and control of robotic manipulators. Through a number of ...

    Guilherme de A. Barreto, Aluizio F. R. Araújo… in Journal of Intelligent and Robotic Systems (2003)