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

Code | Appendix

The proposed approach won the championship of the in-hand manipulation track of the 9th Robotic Grasping and Manipulation Competition (RGMC) held at ICRA 2024. Additionally, it was awarded the Most Elegant Solution among all tracks of the RGMC.

The paper has been submitted to IEEE RA-L.

Video

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, making large-range movements, and 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.

Contact

If you have any question, feel free to contact the authors: Mingrui Yu, mingruiyu98@gmail.com .

Mingrui Yu’s Homepage is at mingrui-yu.github.io.