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Bin-picking[electronic resource] :new approaches for a classical problem /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	621
書名/作者:	Bin-picking : new approaches for a classical problem // by Dirk Buchholz.
作者:	Buchholz, Dirk.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	xv, 117 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Mechatronics.
標題:	Robot vision.
標題:	Detectors.
標題:	Engineering.
標題:	Computational Intelligence.
標題:	Robotics and Automation.
標題:	Image Processing and Computer Vision.
標題:	Artificial Intelligence (incl. Robotics)
ISBN:	9783319265001
ISBN:	9783319264981
內容註:	Introduction - Automation and the Need for Pose Estimation -- Bin-Picking - 5 Decades of Research -- 3D Point Cloud Based Pose Estimation -- Depth Map Based Pose Estimation -- Normal Map Based Pose Estimation -- Summary and Conclusion.
摘要、提要註:	This book is devoted to one of the most famous examples of automation handling tasks - the "bin-picking" problem. To pick up objects, scrambled in a box is an easy task for humans, but its automation is very complex. In this book three different approaches to solve the bin-picking problem are described, showing how modern sensors can be used for efficient bin-picking as well as how classic sensor concepts can be applied for novel bin-picking techniques. 3D point clouds are firstly used as basis, employing the known Random Sample Matching algorithm paired with a very efficient depth map based collision avoidance mechanism resulting in a very robust bin-picking approach. Reducing the complexity of the sensor data, all computations are then done on depth maps. This allows the use of 2D image analysis techniques to fulfill the tasks and results in real time data analysis. Combined with force/torque and acceleration sensors, a near time optimal bin-picking system emerges. Lastly, surface normal maps are employed as a basis for pose estimation. In contrast to known approaches, the normal maps are not used for 3D data computation but directly for the object localization problem, enabling the application of a new class of sensors for bin-picking.
電子資源:	http://dx.doi.org/10.1007/978-3-319-26500-1

Bin-picking[electronic resource] :new approaches for a classical problem /
Buchholz, Dirk.

Bin-pickingnew approaches for a classical problem /[electronic resource] :by Dirk Buchholz. - Cham :Springer International Publishing :2016. - xv, 117 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v.442198-4182 ;. - Studies in systems, decision and control ;v.7..

Introduction - Automation and the Need for Pose Estimation -- Bin-Picking - 5 Decades of Research -- 3D Point Cloud Based Pose Estimation -- Depth Map Based Pose Estimation -- Normal Map Based Pose Estimation -- Summary and Conclusion.

This book is devoted to one of the most famous examples of automation handling tasks - the "bin-picking" problem. To pick up objects, scrambled in a box is an easy task for humans, but its automation is very complex. In this book three different approaches to solve the bin-picking problem are described, showing how modern sensors can be used for efficient bin-picking as well as how classic sensor concepts can be applied for novel bin-picking techniques. 3D point clouds are firstly used as basis, employing the known Random Sample Matching algorithm paired with a very efficient depth map based collision avoidance mechanism resulting in a very robust bin-picking approach. Reducing the complexity of the sensor data, all computations are then done on depth maps. This allows the use of 2D image analysis techniques to fulfill the tasks and results in real time data analysis. Combined with force/torque and acceleration sensors, a near time optimal bin-picking system emerges. Lastly, surface normal maps are employed as a basis for pose estimation. In contrast to known approaches, the normal maps are not used for 3D data computation but directly for the object localization problem, enabling the application of a new class of sensors for bin-picking.

ISBN: 9783319265001

Standard No.: 10.1007/978-3-319-26500-1doiSubjects--Topical Terms:

455721
Mechatronics.

LC Class. No.: TJ163.12

Dewey Class. No.: 621

Bin-picking[electronic resource] :new approaches for a classical problem /
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