Robotic Bin Picking for Potentially Tangled Objects
Author:   Xinyi Zhang ,  Yukiyasu Domae ,  Weiwei Wan ,  Kensuke Harada
Publisher:   Springer International Publishing AG
Edition:   2024 ed.
ISBN:  

9783031674532


Pages:   129
Publication Date:   17 October 2024
Format:   Hardback
Availability:   Not yet available   Availability explained
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Robotic Bin Picking for Potentially Tangled Objects


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Overview

This book introduces methods for bin picking in manufacturing. These methods can be used to develop unified, dexterous, and robust bin picking systems for entangled objects. The target objects include both rigid and deformable objects. Robotic bin picking is a valuable task in manufacturing, aiming to automate the assembly process by utilizing robots to pick necessary objects from disorganized bins. Previous studies have addressed various challenges related to bin picking. However, when objects with complex shapes or deformable properties are randomly placed in a bin, they tend to get entangled, making it difficult for the robot to pick up individual items. This poses challenges in perception, as the robot must be capable of distinguishing between isolated objects and potentially tangled ones in a cluttered environment. This book is of interest to students, researchers, and professionals in manufacturing industries.

Full Product Details

Author:   Xinyi Zhang ,  Yukiyasu Domae ,  Weiwei Wan ,  Kensuke Harada
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2024 ed.
ISBN:  

9783031674532


ISBN 10:   3031674537
Pages:   129
Publication Date:   17 October 2024
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Not yet available   Availability explained
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Background, Introduction and Motivation.- Part I Avoiding Picking Potentially Entangled Objects.- Deep Learning for Classifying Potential Entangled Objects.- Entanglement Map: A Visual Representation for Entangled Objects.- Shape Reconstruction of Entangled Objects.- Part II Disentangling Manipulation Planning for Entangled Objects.- Affordance Maps for Picking or Separating Entangled Objects.- Learning Efficient Policies for Entangled Wire Harnesses.- Dynamic and Bimanual Manipulation with F/T Feedback for Entangled Wire Harnesses.- Conclusions.

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