Surrogate Models for Compliant Joints in Programmable Structures

Abstract This work focuses on compliant joints in autonomous cells. These cells are able to preserve the underlying geometry of a mesh and enable self-reconfiguration through the utilization of six-bar linkages. The six-bar linkages, essential for maintaining triangular mesh geometry, are realized as 3D-printable compliant mechanisms. However, challenges arise from compliance in the hinges and deviation from the desired center of rotation which results in positioning errors. To address these issues, a surrogate model which is derived from beam elements, is used to predict positioning errors during self-reconfiguration. Finally, these errors are corrected by solving the inverse kinematics of a hyper-redundant manipulator. Our study illustrates the benefits of utilizing a surrogate model, which reduces computation time compared to beam elements. For the first time, we successfully correct positioning errors within a system of cells.

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Publication Details

Published
2024-08-25
DOI
https://doi.org/10.1115/detc2024-143600
Citations
2
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.52
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article

Surrogate Models for Compliant Joints in Programmable Structures

Michael Pieber, Johannes Gerstmayr, Peter Manzl, Zhaowei Zhang
2 citations
Topology Optimization in Engineering
0.52
article

Surrogate Models for Compliant Joints in Programmable Structures

Michael Pieber, Johannes Gerstmayr, Peter Manzl, Zhaowei Zhang
article en
2 citations

Abstract

Abstract This work focuses on compliant joints in autonomous cells. These cells are able to preserve the underlying geometry of a mesh and enable self-reconfiguration through the utilization of six-bar linkages. The six-bar linkages, essential for maintaining triangular mesh geometry, are realized as 3D-printable compliant mechanisms. However, challenges arise from compliance in the hinges and deviation from the desired center of rotation which results in positioning errors. To address these issues, a surrogate model which is derived from beam elements, is used to predict positioning errors during self-reconfiguration. Finally, these errors are corrected by solving the inverse kinematics of a hyper-redundant manipulator. Our study illustrates the benefits of utilizing a surrogate model, which reduces computation time compared to beam elements. For the first time, we successfully correct positioning errors within a system of cells.

Shenyang Institute of Automation (CN), Universität Innsbruck (AT)
Openalex Percentile: Top 35%
Topology Optimization in Engineering
0.52
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