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Probabilistic Articulated Real-Time Tracking for Robot Manipulation.

IEEE Robotics and Automation Letters, no. 2 (2017): 577-584

Cited by: 49|Views71
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Abstract

We propose a probabilistic filtering method which fuses joint measurements with depth images to yield a precise, real-time estimate of the end-effector pose in the camera frame. This avoids the need for frame transformations when using it in combination with visual object tracking methods. Precision is achieved by modeling and correcting ...More

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