Abstract
Detecting and localizing objects in three-dimensional space is essential for robotic manipulation. One practical task is known as “bin-picking”, where a robot manipulator picks objects from a bin of parts without any assistance of an operator. For such a task, vision-based object detection and location can be a cost-effective solution. In this paper, we propose a fast and robust approach for picking flanges in a crowd condition. We present a continuous edge detector improved from Canny and a fast ellipse detector based on randomized hough transformation to obtain the outer contours of flange. And then we have implement several picking experiments to verify our proposed approach is fast and robust in practical environment.
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Acknowledgement
This work was supported in part by National Natural Science Foundation of China (No. 81373555), and Shanghai Committee of Science and Technology (14JC1402200 and 14441904403) for funding.
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Luo, L., Luo, Y., Lu, H., Yuan, H., Tang, X., Zhang, W. (2018). Fast Circular Object Localization and Pose Estimation for Robotic Bin Picking. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_52
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DOI: https://doi.org/10.1007/978-3-319-77383-4_52
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