Model-Based Static Compliance Analysis and Control for Pneumatic-Driven Soft Robots
Jialei Shi, Sara-Adela Abad, Ge Shi, Wenlong Gaozhang, Jian S. Dai, Helge Würdemann
- Year
- 2025
- Citations
- 4
Abstract
Elastomer-based soft manipulators have been explored in various fields due to their inherent compliant properties. Understanding and regulation of robot's compliance are important to the design, modeling, and control of soft robots. However, the elastomers are nonlinear hyperelastic materials with distributed compliance. This property makes the compliance modeling and control of soft robots fundamentally different and more complex from their rigid counterparts. This article presents a neo-Hookean model-based compliance modeling and control approach to investigate and regulate the configuration-dependent compliance property of a pneumatic-driven soft manipulator. The neo-Hookean model is used to derive the stretch ratio and update the tangent modulus of materials. The robot's compliance is obtained by integration with the forward kinematics building on the static Cosserat rod model. The derived compliance matrix is utilized to regulate robot's compliance along the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$x$</tex-math></inline-formula>-, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$y$</tex-math></inline-formula>-, and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$z$</tex-math></inline-formula>-axes. Computational and experimental validation demonstrate high fidelity of the proposed approach. Moreover, experiments illustrate that the exhibited robot's compliance can be regulated up to 49.5% higher or 34.2% lower compared to inherent robot's compliance. The proposed model-based compliance control strategy has also demonstrated its effectiveness in enhancing grasping ability when implemented on a soft gripper.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002