@article{Illonen_IJRR_2013,
  title = {3-D Object Reconstruction of Symmetric Objects by Fusing Visual and Tactile Sensing},
  journal = {The International Journal of Robotics Research},
  abstract = {In this work, we propose to reconstruct a complete 3-D model of an unknown object
  by fusion of visual and tactile information while the object is grasped. Assuming the
  object is symmetric, a first hypothesis of its complete 3-D shape is generated. A grasp
  is executed on the object with a robotic manipulator equipped with tactile sensors.
  Given the detected contacts between the fingers and the object, the initial full object
  model including the symmetry parameters can be refined. This refined model will then
  allow the planning of more complex manipulation tasks.
  The main contribution of this work is an optimal estimation approach for the fusion of
  visual and tactile data applying the constraint of object symmetry. The fusion is
  formulated as a state estimation problem and solved with an iterative extended
  Kalman filter. The approach is validated experimentally using both artificial and real
  data from two different robotic platforms.},
  volume = {33},
  number = {2},
  pages = {321-341},
  publisher = {Sage},
  month = oct,
  year = {2013},
  author = {Illonen, J. and Bohg, J. and Kyrki, V.},
  doi = {10.1177/0278364913497816 },
  month_numeric = {10}
}