A Scooping-Binding Robotic Gripper for Handling Various Food Products
Food products are usually difficult to handle for robots because of their large variations in shape, size, softness, and surface conditions. It is ideal to use one robotic gripper to handle as many food products as possible. In this study, a scooping-binding robotic gripper is proposed to achieve th...
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Published in: | Frontiers in robotics and AI Vol. 8; p. 640805 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Switzerland
Frontiers Media S.A
26-03-2021
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Subjects: | |
Online Access: | Get full text |
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Summary: | Food products are usually difficult to handle for robots because of their large variations in shape, size, softness, and surface conditions. It is ideal to use one robotic gripper to handle as many food products as possible. In this study, a scooping-binding robotic gripper is proposed to achieve this goal. The gripper was constructed using a pneumatic parallel actuator and two identical scooping-binding mechanisms. The mechanism consists of a thin scooping plate and multiple rubber strings for binding. When grasping an object, the mechanisms actively makes contact with the environment for scooping, and the object weight is mainly supported by the scooping plate. The binding strings are responsible for stabilizing the grasping by wrapping around the object. Therefore, the gripper can perform high-speed pick-and-place operations. Contact analysis was conducted using a simple beam model and a finite element model that were experimentally validated. Tension property of the binding string was characterized and an analytical model was established to predict binding force based on object geometry and binding displacement. Finally, handling tests on 20 food items, including products with thin profiles and slippery surfaces, were performed. The scooping-binding gripper succeeded in handling all items with a takt time of approximately 4 s. The gripper showed potential for actual applications in the food industry. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Matteo Cianchetti, Sant’Anna School of Advanced Studies, Italy Matthew Aaron Robertson, Queen’s University, Canada Reviewed by: Panagiotis Vartholomeos, TWI-Hellas, Greece This article was submitted to Soft Robotics, a section of the journal Frontiers in Robotics and AI Carlos Blanes, University of Burgos, Spain |
ISSN: | 2296-9144 2296-9144 |
DOI: | 10.3389/frobt.2021.640805 |