Matthias Kerzel

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Tactile maps offer access to spatial-analog information for visually impaired people. In contrast to visual maps, a tactile map has a lower resolution and can only be inspected in a sequential way, complicating the extraction of spatial relations among distant map entities. Verbal assistance can help to overcome these difficulties by substituting textual(More)
Tactile maps are non-visual substitutes for visual maps for blind and visually impaired people. In [3, 11] we suggested to increase the effectiveness of tactile maps by developing a system that generates assisting utterances to facilitate knowledge acquisition. The utterances are inspired by a corpus of assisting utterances given to tactile map explorers by(More)
Human companion robots need to be sociable and responsive towards emotions to better interact with the human environment they are expected to operate in. This paper is based on the Neuro-Inspired COmpanion robot (NICO) and investigates a hybrid, deep neural network model to teach the NICO to associate perceived emotions with expression representations using(More)
We present a novel approach for haptic material classification based on an adaptation of human haptic exploratory procedures executed by a robot arm with an optical force sensor. A multi-channel neural architecture informed by findings from human haptic perception performs a spectral analysis on vibration and texture data gathered during material(More)
Haptic representations offer access to graphical information for blind and visually impaired persons. Haptic perception requires active explorative movements, making haptic perception, in contrast to visual perception, sequential and local. In order to improve the information gain during haptic exploration and to compensate its limitations additional(More)
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