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Depth-Based Visual Servoing Using Low-Accurate Arm
Abstract : This paper proposes a visual-servoing method dedicated to grasping of daily-life objects. In order to obtain an affordable solution, we use a low-accurate robotic arm. Our method corrects errors by using an RGB-D sensor. It is based on SURF invariant features which allows us to perform object recognition at a high frame rate. We define regions of interest based on depth segmentation, and we use them to speed-up the recognition and to improve reliability. The system has been tested on a real-world scenario. In spite of the lack of accuracy of all the components and the uncontrolled environment, it grasps objects successfully on more than 95 percents of the trials.
https://hal.inria.fr/hal-01416248
Contributor : Ludovic Hofer <>
Submitted on : Wednesday, December 14, 2016 - 11:22:13 AM
Last modification on : Monday, November 30, 2020 - 9:30:04 AM
Contributor : Ludovic Hofer <>
Submitted on : Wednesday, December 14, 2016 - 11:22:13 AM
Last modification on : Monday, November 30, 2020 - 9:30:04 AM
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