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Optimizing Out-of-Plane Stiffness for Soft Grippers
- Source :
- Su, R, Tian, Y, Du, M & Wang, C C L 2022, ' Optimizing Out-of-Plane Stiffness for Soft Grippers ', IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10430-10437 . https://doi.org/10.1109/LRA.2022.3193487
- Publication Year :
- 2022
-
Abstract
- In this letter, we presented a data-driven framework to optimize the out-of-plane stiffness for soft grippers to achieve mechanical properties as hard-to-twist and easy-to-bend. The effectiveness of this method is demonstrated in the design of a soft pneumatic bending actuator (SPBA). First, a new objective function is defined to quantitatively evaluate the out-of-plane stiffness as well as the bending performance. Then, sensitivity analysis is conducted on the parametric model of an SPBA design to determine the optimized design parameters with the help of Finite Element Analysis (FEA). To enable the computation of numerical optimization, a data-driven approach is employed to learn a cost function that directly represents the out-of-plane stiffness as a differentiable function of the design variables. A gradient-based method is used to maximize the out-of-plane stiffness of the SPBA while ensuring specific bending performance. The effectiveness of our method has been demonstrated in physical experiments taken on 3D-printed grippers.
- Subjects :
- FOS: Computer and information sciences
soft robotics
Control and Optimization
Mechanical Engineering
Biomedical Engineering
design optimization
Computer Science Applications
Human-Computer Interaction
Computer Science::Robotics
Computer Science - Robotics
out-of-plane stiffness
Data-driven optimization
stable grasping
Artificial Intelligence
Control and Systems Engineering
Computer Vision and Pattern Recognition
Robotics (cs.RO)
ComputingMethodologies_COMPUTERGRAPHICS
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Su, R, Tian, Y, Du, M & Wang, C C L 2022, ' Optimizing Out-of-Plane Stiffness for Soft Grippers ', IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10430-10437 . https://doi.org/10.1109/LRA.2022.3193487
- Accession number :
- edsair.doi.dedup.....4a5704d54242d28708c604f21454a728
- Full Text :
- https://doi.org/10.1109/LRA.2022.3193487