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Studies in Systems, Decision and Control

Bin-Picking

New Approaches for a Classical Problem

Authors: Buchholz, Dirk

  • Presents three full approaches to solve the bin-picking problem: based on normal maps, using depth maps, and based on point clouds in combination with depth maps
  • Explains the three approaches in detail and in connection to each other, while individual chapters are also understandable on their own
  • Serves as introduction to bin-picking and pose estimation
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Buy this book

eBook $69.99
price for USA (gross)
valid through October 16, 2017
  • ISBN 978-3-319-26500-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $99.00
price for USA
valid through October 16, 2017
  • ISBN 978-3-319-26498-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

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.

Table of contents (6 chapters)

  • Introduction—Automation and the Need for Pose Estimation

    Buchholz, Dirk

    Pages 1-2

  • Bin-Picking—5 Decades of Research

    Buchholz, Dirk

    Pages 3-12

  • 3D Point Cloud Based Pose Estimation

    Buchholz, Dirk

    Pages 13-37

  • Depth Map Based Pose Estimation

    Buchholz, Dirk

    Pages 39-56

  • Normal Map Based Pose Estimation

    Buchholz, Dirk

    Pages 57-95

Buy this book

eBook $69.99
price for USA (gross)
valid through October 16, 2017
  • ISBN 978-3-319-26500-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $99.00
price for USA
valid through October 16, 2017
  • ISBN 978-3-319-26498-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Bin-Picking
Book Subtitle
New Approaches for a Classical Problem
Authors
Series Title
Studies in Systems, Decision and Control
Series Volume
44
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing Switzerland
eBook ISBN
978-3-319-26500-1
DOI
10.1007/978-3-319-26500-1
Hardcover ISBN
978-3-319-26498-1
Series ISSN
2198-4182
Edition Number
1
Number of Pages
XV, 117
Number of Illustrations and Tables
40 b/w illustrations, 23 illustrations in colour
Topics