Bio-Inspired Topology Optimization Framework for Flexible Robotic Grippers

Abstract This study aims to promote the concept that integrating biomimetic design and topology optimization is a key direction for the further advancement of flexible robotic grippers. Biomimetic design is an efficient approach to innovate flexible gripper configurations. Although the functions of biological tissues and industrial equipment can be similar, they are not entirely consistent. Merely mimicking biological forms can hinder structural innovation. Therefore, it is necessary to optimize bio-inspired grippers based on practical industrial requirements. This study proposes abstracting the bio-inspired design domain and boundary conditions from the Fin Ray® effect. Topology optimization methods are then employed to update the flexible grippers further. The combination of topology optimization and a biomimetic initial configuration significantly promotes flexible grippers. Additionally, new solutions for explicit modeling and element distortion are established to stabilize the optimization. Based on these studies, a topology optimization framework for the flexible gripper is developed. Experiments indicate that the optimized gripper can grasp objects of various sizes, shapes, and materials. The maximum payload of the proposed gripper reaches 2425.3 g with only 60 N input force. Compared with the classic Fin Ray® gripper, the proposed gripper exhibits 42.7–87.5% increases in gripping force and an 82.9% increase in the maximum payload. Compared to classic topology optimization designs, bio-inspired topology optimization increases the maximum payload by at least 67.3%. Therefore, topology optimization and biomimetic design are highly complementary, and their integration is critical to future innovations in flexible robotics.

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Publication Details

Journal
Journal of Mechanical Design
Published
2025-05-01
DOI
https://doi.org/10.1115/1.4068552
Primary Topic
Robotic Mechanisms and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Bio-Inspired Topology Optimization Framework for Flexible Robotic Grippers

Baotong Li, Jun Hong, Honglei Liu, Wenjie Su
Journal of Mechanical Design
Robotic Mechanisms and Dynamics
article

Bio-Inspired Topology Optimization Framework for Flexible Robotic Grippers

Baotong Li, Jun Hong, Honglei Liu, Wenjie Su
article en

Abstract

Abstract This study aims to promote the concept that integrating biomimetic design and topology optimization is a key direction for the further advancement of flexible robotic grippers. Biomimetic design is an efficient approach to innovate flexible gripper configurations. Although the functions of biological tissues and industrial equipment can be similar, they are not entirely consistent. Merely mimicking biological forms can hinder structural innovation. Therefore, it is necessary to optimize bio-inspired grippers based on practical industrial requirements. This study proposes abstracting the bio-inspired design domain and boundary conditions from the Fin Ray® effect. Topology optimization methods are then employed to update the flexible grippers further. The combination of topology optimization and a biomimetic initial configuration significantly promotes flexible grippers. Additionally, new solutions for explicit modeling and element distortion are established to stabilize the optimization. Based on these studies, a topology optimization framework for the flexible gripper is developed. Experiments indicate that the optimized gripper can grasp objects of various sizes, shapes, and materials. The maximum payload of the proposed gripper reaches 2425.3 g with only 60 N input force. Compared with the classic Fin Ray® gripper, the proposed gripper exhibits 42.7–87.5% increases in gripping force and an 82.9% increase in the maximum payload. Compared to classic topology optimization designs, bio-inspired topology optimization increases the maximum payload by at least 67.3%. Therefore, topology optimization and biomimetic design are highly complementary, and their integration is critical to future innovations in flexible robotics.

Journal of Mechanical DesignVol. 148(1)
Xi'an Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 90%
Robotic Mechanisms and Dynamics
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Bio-Inspired Topology Optimization Framework for Flexible Robotic Grippers — Baotong Li, Jun Hong, et al. · Journal of Mechanical Design (2025) | TGRS Research Map | TGRS