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ROBOMECH Journal
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ROBOMECH Journal
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Caging-based grasping of deformable objects for geometry-based robotic manipulation

Authors: Dabae Kim; Yusuke Maeda; Shun Komiyama;

Caging-based grasping of deformable objects for geometry-based robotic manipulation

Abstract

Abstract In this paper, we present a novel method for caging-based grasping of deformable objects. This method enables manipulators to grasp objects simply with geometric constraints by using position control of robotic hands, and not through force controls or mechanical analysis. Therefore, this method has cost benefits and algorithmic simplicity. In our previous studies, we mainly focused on caging-based grasping of rigid objects such as 2D/3D primitive-shaped objects. However, considering realistic objects, manipulation of deformable objects is also required frequently. Hence, this study is motivated to manipulate deformable objects, adopting a caging-based grasping approach. We formulate caging-based grasping of deformable objects, and target three types of deformable objects: a rigid object covered with a soft part, a closed-loop structure, and two rigid bodies connected with a string, which can be regarded as primitive shapes. We then derive concrete conditions for grasp synthesis and conduct experimental verification of our proposed method with an industrial manipulator.

Keywords

Technology, Grasping, Deformable objects, Control engineering systems. Automatic machinery (General), Caging-based grasping, Industrial engineering. Management engineering, T, Information technology, T55.4-60.8, T58.5-58.64, T59.5, Caging, Automation, Robotic manipulation, TJ212-225, TJ1-1570, T1-995, Mechanical engineering and machinery, TJ227-240, Machine design and drawing, Technology (General)

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
gold