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Conference Papers Year : 2016

Depth-Based Visual Servoing Using Low-Accurate Arm


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.

Dates and versions

hal-01416248 , version 1 (14-12-2016)



Ludovic Hofer, Michio Tanaka, Hakaru Tamukoh, Amir Ali Forough Nassiraei, Takashi Morie. Depth-Based Visual Servoing Using Low-Accurate Arm. Joint 8th International Conference on Soft Computing and Intelligent Systems and 17th International Symposium on Advanced Intelligent Systems, Aug 2016, Sapporo, Japan. ⟨hal-01416248⟩


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