@InProceedings{agravante:iros:2013,
  author    = {Agravante, Don Joven and Cherubini, Andrea and Bussy, Antoine and Kheddar, Abderrahmane},
  title     = {Human-Humanoid Joint Haptic Table Carrying Task with Height Stabilization using Vision},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year      = {2013},
  address   = {Tokyo, Japan},
  month     = {November 3-November 7},
  url       = {https://hal-lirmm.ccsd.cnrs.fr/lirmm-00857659/document},
  keywords  = {Force, Legged locomotion, Impedance, Visualization, Joints, Torque},
  doi       = {10.1109/IROS.2013.6697019},
  abstract  = {In this paper, a first step is taken towards using vision in human-humanoid haptic joint actions. Haptic joint actions are characterized by physical interaction throughout the execution of a common goal. Because of this, most of the focus is on the use of force/torque-based control. However, force/torque information is not rich enough for some tasks. Here, a particular case is shown: height stabilization during table carrying. To achieve this, a visual servoing controller is used to generate a reference trajectory for the impedance controller. The control law design is fully described along with important considerations for the vision algorithm and a framework to make pose estimation robust during the table carrying task of the humanoid robot. We then demonstrate all this by an experiment where a human and the HRP-2 humanoid jointly transport a beam using combined force and vision data to adjust the interaction impedance while at the same time keeping the inclination of the beam horizontal.}
}