Conference proceeding
Mechanical stiffness augmentation of a 3D printed soft prosthetic finger
2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Vol.2016-, pp.7-12
2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) (Banff, Alberta, Canada, 12/07/2016–15/07/2016)
07/2016
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Abstract
Soft robotics, as a multi-disciplinary research area, has recently gained a significant momentum due to offering unconventional characteristics relative to rigid robots such as a resilient, highly dexterous, compliant and safer interaction with humans and their physical environments. However, soft robots suffer from not being able to carry their own weight which mainly depends on the modulus of elasticity of the material used to fabricate them. In this paper, we report on a practical and easy-to-implement stiffness augmentation method to enhance stiffness of soft robotic components. We fabricated a soft robotic finger which is fully compliant with flexure hinges using Fused Deposition Modelling (FDM) technique and a stiffness augmenting unit made of thin poly(vinyl chloride)(PVC) sheets. The stiffness of the entire robotic finger was increased mechanically by linearly driving the stiffness augmenting unit. The experimental data presented show that stiffness of the finger was increased by 40 %. Depending on the material properties and thickness used for fabricating the stiffness augmenting unit, a higher rate of stiffness increase can be easily obtained.
Details
- Title
- Mechanical stiffness augmentation of a 3D printed soft prosthetic finger
- Creators
- Rahim Mutlu - University of WollongongS. Kumbay Yildiz - University of WollongongGursel Alici - University of WollongongMarc in het Panhuis - University of WollongongGeoff M. Spinks - University of Wollongong
- Publication Details
- 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Vol.2016-, pp.7-12
- Conference
- 2016 IEEE International Conference on Advanced Intelligent Mechatronics (AIM) (Banff, Alberta, Canada, 12/07/2016–15/07/2016)
- Publisher
- IEEE
- Number of pages
- 6
- Identifiers
- 991013225778702368
- Copyright
- © Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.
- Academic Unit
- Faculty of Science and Engineering
- Language
- English
- Resource Type
- Conference proceeding