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Fusion de données multicapteurs pour la capture de mouvement

Abstract : This thesis deals with motion capture (MoCap) which goal is to acquire the attitude of human's body. In our case, the arm and the leg are considered. The MoCap trackers are made of "software" and "hardware" parts which allow acquisition of the movement of an object or a human in space in real or differed time. Many MoCaps systems still exist, but they require an adaptation of the environment. In this thesis, a low cost, low weight attitude central unit (UCN namely a triaxes magnetometer and a triaxes accelerometer), is used. This attitude central unit has been developed within the CEA-LETI. In this work, we propose different algorithms to estimate the attitude and the linear accelerations of a rigid body. For the rotation parametrization, the unit quaternion is used. Firstly, the estimation of the attitude and the accelerations (6DDL case) from the measurements provided by ACU is done via an optimization technique. The motion capture of articulated chains (arm and leg) is also studied with ad-hoc assumptions on the accelerations in the pivot connections, the orientation of the segments as well as the accelerations in particular points of the segments can be estimated. The different approaches proposed in this work have been evaluated with simulated data and real data.
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Contributor : Bernardino Benito Salmeron-Quiroz <>
Submitted on : Tuesday, May 22, 2007 - 5:55:07 PM
Last modification on : Thursday, November 19, 2020 - 12:59:39 PM
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  • HAL Id : tel-00148577, version 1


Bernardino Benito Salmeron-Quiroz. Fusion de données multicapteurs pour la capture de mouvement. Automatique / Robotique. Université Joseph-Fourier - Grenoble I, 2007. Français. ⟨tel-00148577⟩



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