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Model-based strategy for grasping 3 D deformable objects using a multi-fingered robotic hand
This paper presents a model-based strategy for 3D deformable object grasping using a multi-fingered robotic hand. The developed contact model is based on two force components (normal force and tangential friction force, including slipping and sticking effects) and uses a non-linear mass-spring syste...
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Published in: | Robotics and autonomous systems 2017-09, Vol.95, p.196-206 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | This paper presents a model-based strategy for 3D deformable object grasping using a multi-fingered robotic hand. The developed contact model is based on two force components (normal force and tangential friction force, including slipping and sticking effects) and uses a non-linear mass-spring system to describe the object deformations due the mechanical load applied by the fingers of the robotic hand. The object-finger interaction is simulated in order to compute the required contact forces and deformations to robustly grasp objects with large deformations. Our approach is able to achieve this by using a non-linear model that outperforms current techniques that are limited to using linear models. After the contact forces computed by the simulation of the contact model guarantee the equilibrium of the grasp, they will be used as set-points for force-controlling the closing of the real fingers, and thus, the proposed grasping strategy is implemented. Two different objects (cube and sphere) made from two soft materials (foam and rubber) are tested in order to verify that the proposed model can represent their non-linear deformations and that the proposed grasp strategy can implement a robust grasp of them with a multi-fingered robotic hand equipped with tactile sensors. Thereby, both the grasping strategy and the proposed contact model are validated experimentally. |
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ISSN: | 0921-8890 1872-793X |
DOI: | 10.1016/j.robot.2017.06.011 |