Robotic In-Hand Manipulation for Large-Range Precise Object Movement: The RGMC Champion Solution

In-hand manipulation using multiple dexterous fingers is a critical robotic skill that can reduce the reliance on large arm motions, thereby saving space and energy. This letter focuses on in-grasp object movement, which refers to manipulating an object to a desired pose through only finger motions within a stable grasp. The key challenge lies in simultaneously achieving high precision and large-range movements while maintaining a constant stable grasp. To address this problem, we propose a simple and practical approach based on kinematic trajectory optimization with no need for pretraining or object geometries, which can be easily applied to novel objects in real-world scenarios. Adopting this approach, we won the championship for the in-hand manipulation track at the 9th Robotic Grasping and Manipulation Competition (RGMC) held at ICRA 2024. Implementation details, discussion, and further quantitative experimental results are presented in this letter, which aims to comprehensively evaluate our approach and share our key takeaways from the competition.

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Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2025-03-27
DOI
https://doi.org/10.1109/lra.2025.3555138
Citations
6
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
7.29
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article

Robotic In-Hand Manipulation for Large-Range Precise Object Movement: The RGMC Champion Solution

Yongpeng Jiang, Mingrui Yu, Chen Chen, Yongyi Jia et al.
6 citations
IEEE Robotics and Automation Letters
Robot Manipulation and Learning
7.29
article

Robotic In-Hand Manipulation for Large-Range Precise Object Movement: The RGMC Champion Solution

Yongpeng Jiang, Mingrui Yu, Chen Chen, Yongyi Jia, Li Xiang
article en
6 citations

Abstract

In-hand manipulation using multiple dexterous fingers is a critical robotic skill that can reduce the reliance on large arm motions, thereby saving space and energy. This letter focuses on in-grasp object movement, which refers to manipulating an object to a desired pose through only finger motions within a stable grasp. The key challenge lies in simultaneously achieving high precision and large-range movements while maintaining a constant stable grasp. To address this problem, we propose a simple and practical approach based on kinematic trajectory optimization with no need for pretraining or object geometries, which can be easily applied to novel objects in real-world scenarios. Adopting this approach, we won the championship for the in-hand manipulation track at the 9th Robotic Grasping and Manipulation Competition (RGMC) held at ICRA 2024. Implementation details, discussion, and further quantitative experimental results are presented in this letter, which aims to comprehensively evaluate our approach and share our key takeaways from the competition.

IEEE Robotics and Automation LettersVol. 10(5)
Tsinghua University (CN)
Openalex Percentile: Top 3%
Robot Manipulation and Learning
7.29
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Robotic In-Hand Manipulation for Large-Range Precise Object Movement: The RGMC Champion Solution — Yongpeng Jiang, Mingrui Yu, et al. · IEEE Robotics and Automation Letters (2025) | TGRS Research Map | TGRS