Titlebook: Bin-Picking; New Approaches for a Dirk Buchholz Book 2016 Springer International Publishing Switzerland 2016 3D Point Clouds.Bin-Picking.Co

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Italian Academies and Their Facebooks,tables. After successful localization, a collision avoidance mechanism is introduced reducing the problem’s complexity by interpreting the point clouds as depth maps and using 2D image analysis. The chapter is concluded by the presentation of experiments demonstrating the potential of the approach.

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https://doi.org/10.1007/978-3-319-74757-6shots. By analyzing normal histograms (Extended Gaussian Images) the orientation is computed, to then get the position. The position estimation is described in 2 different ways, one two step and one single step approach which is capable of delivering accurate positions using a monocular camera. Expe

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,Introduction—Automation and the Need for Pose Estimation,In this chapter, the topic of the book is introduced. It is explained, how object pose estimation is the basis of many automation tasks. The bin-picking problem as one of the famous examples of robotic automation is shortly introduced.

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3D Point Cloud Based Pose Estimation,tables. After successful localization, a collision avoidance mechanism is introduced reducing the problem’s complexity by interpreting the point clouds as depth maps and using 2D image analysis. The chapter is concluded by the presentation of experiments demonstrating the potential of the approach.

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Depth Map Based Pose Estimation,r very efficient scene analysis. An approach is described how grasp poses on unknown objects can be computed in real-time allowing for near time optimal grasping. It is further described how the approach can be extended for bin-picking tasks of known objects by combining the visual scene analysis wi