4.6 Article

Viko 2.0: A Hierarchical Gecko-Inspired Adhesive Gripper With Visuotactile Sensor

Journal

IEEE ROBOTICS AND AUTOMATION LETTERS
Volume 7, Issue 3, Pages 7842-7849

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2022.3183249

Keywords

Biologically-inspired robots; force and tactile sensing; grasping; grippers and other end-effectors; perception for grasping and manipulation

Categories

Funding

  1. Hong Kong Innovation and Technology Fund (ITF) [ITS-104-19FP]
  2. Research Grants Council of Hong Kong [16200919]
  3. Hong Kong PhD. Fellowship Scheme [PF18-21218]

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This paper introduces a new adaptive gecko gripper called Viko 2.0, which effectively combines the advantages of adhesives and visuotactile sensors to solve the difficulty of grasping large objects for robotic grippers. Compared with a non-hierarchical structure, the hierarchical structure with a multi-material design achieves a significant increase in adhesion and contact area, while the integrated visuotactile sensor can measure contact area, shear force, and incipient slip detection in real-time.
Robotic grippers with visuotactile sensors have access to rich tactile information for grasping tasks but encounter difficulty in partially encompassing large objects with sufficient grip force. While hierarchical gecko-inspired adhesives are a potential technique for bridging performance gaps, they require a large contact area for efficient usage. In this work, we present a new version of an adaptive gecko gripper called Viko 2.0 that effectively combines the advantage of adhesives and visuotactile sensors. Compared with a non-hierarchical structure, a hierarchical structure with a multi-material design achieves approximately a 1.5 times increase in normal adhesion and double in contact area. The integrated visuotactile sensor captures a deformation image of the hierarchical structure and provides a real-time measurement of contact area, shear force, and incipient slip detection at 24 Hz. The gripper is implemented on a robotic arm to demonstrate an adaptive grasping pose based on contact area, and grasps objects with a wide range of geometries and textures.

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