Centimeter‐Scale Magneto‐Reconfigurable Parallel Robots: A Grassmann Line Geometry Synthesis Framework for Multitask Adaptation Using Magneto‐Connected Part Library

The development of centimeter‐scale reconfigurable parallel robots is critical for applications requiring precise, adaptive, and space‐constrained operations across bench‐top automation and minimally invasive systems. However, existing platforms struggle to balance miniaturization, multidegree‐of‐freedom flexibility, and rapid in situ reconfiguration for different tasks. To address these challenges, Grassmann Line‐Guided Magneto‐Operative Robotics is proposed, a systematic design framework that synergizes Grassmann line geometry with modular magnetic spherical joint connections to enable rapid in situ topology changes. A synthesis‐based method is employed to guide the assembly strategy design flow for a specific magneto‐connected parallel robot. The magneto‐coupled modules enable in situ minute‐level (average 48 s) reconfiguration across multiple types of centimeter‐scale magneto‐reconfigurable parallel robots, all sharing a common driving system and featuring a base diameter of 3.2 cm. As a case study, a widely used 3‐P(4S) robot system is fully analyzed. The regular workspace, considering the influence of magnetic connections and the global transmission index, is evaluated to assess the performance of different design parameters. Then, the payload experiment is conducted. Bench‐top positioning, bench‐top manipulation, and laparoscopic manipulation potentials are demonstrated. Overall, the proposed library and design methodology, utilizing magneto‐connected parts, enable the rapid prototyping of reconfigurable, modular parallel robots.

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Publication Details

Journal
Advanced Intelligent Systems
Published
2025-08-12
DOI
https://doi.org/10.1002/aisy.202500529
Citations
2
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
1.43

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article

Centimeter‐Scale Magneto‐Reconfigurable Parallel Robots: A Grassmann Line Geometry Synthesis Framework for Multitask Adaptation Using Magneto‐Connected Part Library

Yunong Li, Hongliang Ren, Zhiwei Fang, Wenchao Yue et al.
2 citations
Advanced Intelligent Systems
Modular Robots and Swarm Intelligence
1.43
article

Centimeter‐Scale Magneto‐Reconfigurable Parallel Robots: A Grassmann Line Geometry Synthesis Framework for Multitask Adaptation Using Magneto‐Connected Part Library

Yunong Li, Hongliang Ren, Zhiwei Fang, Wenchao Yue, Xiao Xiao, Bin Zhu
article en
2 citations

Abstract

The development of centimeter‐scale reconfigurable parallel robots is critical for applications requiring precise, adaptive, and space‐constrained operations across bench‐top automation and minimally invasive systems. However, existing platforms struggle to balance miniaturization, multidegree‐of‐freedom flexibility, and rapid in situ reconfiguration for different tasks. To address these challenges, Grassmann Line‐Guided Magneto‐Operative Robotics is proposed, a systematic design framework that synergizes Grassmann line geometry with modular magnetic spherical joint connections to enable rapid in situ topology changes. A synthesis‐based method is employed to guide the assembly strategy design flow for a specific magneto‐connected parallel robot. The magneto‐coupled modules enable in situ minute‐level (average 48 s) reconfiguration across multiple types of centimeter‐scale magneto‐reconfigurable parallel robots, all sharing a common driving system and featuring a base diameter of 3.2 cm. As a case study, a widely used 3‐P(4S) robot system is fully analyzed. The regular workspace, considering the influence of magnetic connections and the global transmission index, is evaluated to assess the performance of different design parameters. Then, the payload experiment is conducted. Bench‐top positioning, bench‐top manipulation, and laparoscopic manipulation potentials are demonstrated. Overall, the proposed library and design methodology, utilizing magneto‐connected parts, enable the rapid prototyping of reconfigurable, modular parallel robots.

Advanced Intelligent SystemsVol. 8(1)
Chinese University of Hong Kong (HK), University of Warwick (GB), Shenzhen Academy of Robotics (CN)
Impact Fund, National Natural Science Foundation of China, Chinese University of Hong Kong, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 18%
Modular Robots and Swarm Intelligence
1.43
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