Human-Humanoid Joint Haptic Table Carrying Task with Height Stabilization using Vision

Don Joven Agravante 1 Andrea Cherubini 1 Antoine Bussy 2, 1 Abderrahmane Kheddar 1, 2
1 IDH - Interactive Digital Humans
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
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.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00857659
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Submitted on : Tuesday, September 3, 2013 - 6:52:22 PM
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Don Joven Agravante, Andrea Cherubini, Antoine Bussy, Abderrahmane Kheddar. Human-Humanoid Joint Haptic Table Carrying Task with Height Stabilization using Vision. IROS: Intelligent RObots and Systems, Nov 2013, Tokyo, Japan. ⟨lirmm-00857659⟩

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