Optimal Design of a Compliant Constant-Force Mechanism to Deliver a Nearly Constant Output Force over a Range of Input Displacements

Chih Hsing Liu, Mao Cheng Hsu, Ta Lun Chen, Yang Chen

研究成果: Article同行評審

14 引文 斯高帕斯(Scopus)

摘要

This study presents an optimal design procedure, including topology and geometry optimization methods to design a compliant constant-force mechanism, which can generate a nearly constant output force over a range of input displacements. The proposed constant-force mechanism is a passive force regulation device that can be used in various applications such as precision manipulation and overload protection. The numerical optimization problem is treated as an error minimization problem between output and objective forces. Both material and geometric nonlinearities are considered in topology and geometry optimization steps. Although the element stiffness for void and gray elements after topology optimization are quite small comparing with solid elements, their existence also contributes to the output force characteristic of the synthesized mechanisms. As these low-stiffness elements are not easy to manufacture in physical prototype, a helical compression spring is introduced in the topology optimized constant-force mechanism to account for the effect of low-stiffness elements, and an additional geometry optimization step is utilized to identify the spring constant as well as to fine-tune the geometric parameters. The optimized constant-force mechanism is prototyped by three-dimensional printing using flexible thermoplastic elastomer. The experimental results show that the proposed design can generate a nearly constant output force in the input displacement range of 3-6 mm. The developed constant-force mechanism is installed on an electric gripper drive mounted on a robot arm for robotic picking and placing application. Test results show the constant-force gripper can be used in handling of size-varied fragile objects.

原文English
頁(從 - 到)758-769
頁數12
期刊Soft Robotics
7
發行號6
DOIs
出版狀態Published - 2020 12月

All Science Journal Classification (ASJC) codes

  • 控制與系統工程
  • 生物物理學
  • 人工智慧

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