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

Dabae Kim, Yusuke Maeda, Shun Komiyama

Year
2019
Citations
13

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

GRASPComputer scienceArtificial intelligenceComputer visionObject (grammar)Position (finance)Manipulator (device)Robot

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