A fractal gripper with switchable mode for geometry adaptive manipulation

Despite thriving development in academic and practical scenarios, multi-joint underactuated manipulators is still struggling with grasp stability, especially in case of heavy or irregular-shaped objects. A gripper with fractal morphology is invented to improve the grasping capacity of multi-joint underactuated manipulators. Combining the adaptivity of fractal geometry and the principle of lever, the invented fractal gripper achieves superior grasping capacity. The self-recovery feature is realized by resilient design to activate the function of continuous robust grasping and improve the grasping efficiency. Besides, the grasped objects can be held softly owing to the contact force redistribution and pressure re-equilibrium. Meanwhile, the fractal finger is wrapped by elastic polymer to ensure a safe and secure grasp. Fractal gripper with switchable mode promote its applicability. In the fingertip pressure experiments, we tested the fractal gripper and demonstrated its ability to stably envelop complex objects while ensuring even force distribution. Well-designed grab experiments with objects of diverse shapes and sizes demonstrate the multi-scale adaptability and superior grasping stability of the fractal gripper. Our study brings a transformative design paradigm to integrate traditional machine design with mathematical and mechanical principles, which meets critical requirements from a broader field of practical scenarios, such as dealing with irregular heavy objects in everyday housework, agricultural harvesting and underwater operations.

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Publication Details

Journal
Scientific Reports
Published
2025-04-26
DOI
https://doi.org/10.1038/s41598-025-98752-z
Citations
2
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
2.43

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article

A fractal gripper with switchable mode for geometry adaptive manipulation

Jian Shen, Yan‐Bo Guo, Zhigong Song, Yilin Zheng et al.
2 citations
Scientific Reports
Robot Manipulation and Learning
2.43
article

A fractal gripper with switchable mode for geometry adaptive manipulation

Jian Shen, Yan‐Bo Guo, Zhigong Song, Yilin Zheng, Jiaxin Huang
article en
2 citations

Abstract

Despite thriving development in academic and practical scenarios, multi-joint underactuated manipulators is still struggling with grasp stability, especially in case of heavy or irregular-shaped objects. A gripper with fractal morphology is invented to improve the grasping capacity of multi-joint underactuated manipulators. Combining the adaptivity of fractal geometry and the principle of lever, the invented fractal gripper achieves superior grasping capacity. The self-recovery feature is realized by resilient design to activate the function of continuous robust grasping and improve the grasping efficiency. Besides, the grasped objects can be held softly owing to the contact force redistribution and pressure re-equilibrium. Meanwhile, the fractal finger is wrapped by elastic polymer to ensure a safe and secure grasp. Fractal gripper with switchable mode promote its applicability. In the fingertip pressure experiments, we tested the fractal gripper and demonstrated its ability to stably envelop complex objects while ensuring even force distribution. Well-designed grab experiments with objects of diverse shapes and sizes demonstrate the multi-scale adaptability and superior grasping stability of the fractal gripper. Our study brings a transformative design paradigm to integrate traditional machine design with mathematical and mechanical principles, which meets critical requirements from a broader field of practical scenarios, such as dealing with irregular heavy objects in everyday housework, agricultural harvesting and underwater operations.

Scientific ReportsVol. 15(1)
Jiangnan University (CN), Wuxi Guolian Development (China) (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 12%
Robot Manipulation and Learning
2.43
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A fractal gripper with switchable mode for geometry adaptive manipulation — Jian Shen, Yan‐Bo Guo, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS