Design and Kinetostatic Analysis of PneuNets-Actuated Compliant Mechanisms for Soft Robots

Abstract Designing soft robots is challenging due to their infinite degrees of freedom and high flexibility, which limits their payload capacity. This paper presents a systematic framework for designing and analyzing compliant mechanisms driven by PneuNets bending actuators. The stiffness ratio of the compliant mechanism allows soft robots to carry higher payloads. We design two compliant joints–revolute and prismatic–and verify them through finite element simulations and physical prototypes. A kinetostatic model for the single joint, based on machine learning and the Pseudo-rigid-body model, is developed and integrated into the robotic system. A 3R planar robotic arm is used to evaluate the design and analysis models. The results show that the error of the kinetostatic model is below 5%, and the robotic arm can continuously control target positions with an error of less than 0.5.

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Publication Details

Journal
Journal of Mechanisms and Robotics
Published
2026-07-28
DOI
https://doi.org/10.1115/1.4072406
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
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article

Design and Kinetostatic Analysis of PneuNets-Actuated Compliant Mechanisms for Soft Robots

Hai‐Jun Su, Yi Jin
Journal of Mechanisms and Robotics
Soft Robotics and Applications
article

Design and Kinetostatic Analysis of PneuNets-Actuated Compliant Mechanisms for Soft Robots

Hai‐Jun Su, Yi Jin
article en

Abstract

Abstract Designing soft robots is challenging due to their infinite degrees of freedom and high flexibility, which limits their payload capacity. This paper presents a systematic framework for designing and analyzing compliant mechanisms driven by PneuNets bending actuators. The stiffness ratio of the compliant mechanism allows soft robots to carry higher payloads. We design two compliant joints–revolute and prismatic–and verify them through finite element simulations and physical prototypes. A kinetostatic model for the single joint, based on machine learning and the Pseudo-rigid-body model, is developed and integrated into the robotic system. A 3R planar robotic arm is used to evaluate the design and analysis models. The results show that the error of the kinetostatic model is below 5%, and the robotic arm can continuously control target positions with an error of less than 0.5.

Journal of Mechanisms and Robotics
Great Lakes NeuroTechnologies (United States) (US), The Ohio State University (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 16%
Soft Robotics and Applications
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Design and Kinetostatic Analysis of PneuNets-Actuated Compliant Mechanisms for Soft Robots — Hai‐Jun Su, Yi Jin · Journal of Mechanisms and Robotics (2026) | TGRS Research Map | TGRS