@Article{guiatni:ptve:2009,
  author    = {Guiatni, Mohamed and Benallegue, Abdelaziz and Kheddar, Abderrahmane},
  title     = {Thermal display for telepresence based on neural identification and heat flux servoing},
  journal   = {Presence-Teleoperators and Virtual Environments},
  year      = {2009},
  volume    = {18},
  number    = {2},
  pages     = {156--169},
  month     = {April},
  doi       = {https://doi.org/10.1162/pres.18.2.156},
  abstract  = {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\textquotesingle s thermal display. To do so, two databases are built from real measurements recorded during direct contact between the operator\textquotesingle 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},
  publisher = {MIT PRESS},
  address   = {ONE ROGERS ST, CAMBRIDGE, MA 02142-1209 USA}
}