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The knowledge of the pose and the orientation of mobile robot in its operating environment is of utmost importance for an autonomous robot. In this paper, we present a new robot localization method integrates distributed vision sensors with Monte Carlo localization (MCL) method. Firstly, an improved MCL method is used to estimates the posterior distribution of robot poses conditioned on sensor data...
In this paper, a novel approach is proposed to recover human body pose from 3D voxel data. The use of voxel data leads to viewpoint-free estimation, which benefits in that reconstruction of a training model is needless in different multi-camera arrangements. Other notable aspects of our approach are real-time ensuring speed (up to 30[FPS]), flexibility towards various complex motions, and robustness...
This paper proposes an object recognition and gripping pose estimation approach based on on-line estimation of the complete set of inertial parameters, i.e. the mass, the coordinates of the center of mass, and the elements of the inertia matrix, of an object gripped by or attached to a manipulator. A multi-sensor fusion approach combining 6D force/torque, 6D acceleration, 3D angular velocity, and...
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