Introduction to the theory of neural computation
Introduction to the theory of neural computation
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
The Psychophysics of Temperature Perception and Thermal-Interface Design
HAPTICS '02 Proceedings of the 10th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
Material Discrimination and Thermal Perception
HAPTICS '03 Proceedings of the 11th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (HAPTICS'03)
Thermal Model for Hand-Object Interactions
VR '06 Proceedings of the IEEE conference on Virtual Reality
Fundamentals of Heat and Mass Transfer
Fundamentals of Heat and Mass Transfer
Infrared Thermal Measurement System for Evaluating Model-Based Thermal Displays
WHC '07 Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
Warm or Cool, Large or Small? The Challenge of Thermal Displays
IEEE Transactions on Haptics
Teleoperation based on the hidden robot concept
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Explorative research on the heat as an expression medium: focused on interpersonal communication
Personal and Ubiquitous Computing
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We present a new approach for thermal rendering in telepresence which improves transparency; it aims at reaching, as closely as possible, what is experienced in similar direct touch conditions. Our method is based on a neural networks learning classifier that allows generating appropriate thermal values (i.e., time trajectories) used as desired inputs of two independent controllers: the one controlling a bio-inspired remote thermal sensing device (i.e., an artificial finger), and the other one controlling the user's thermal display. To do so, two databases are built from real measurements recorded during direct contact between the operator's finger and different materials. One database is used for training a classifier to be used in online identification of the material being remotely explored; the other is used to generate desired thermal trajectories for the previously evoked control loops. The learning bloc is based on principal component analysis and a feed-forward neural network. Experimental tests validating our method in different scenarios have been carried out; the obtained results are discussed.