EA-SoGripper: Electroadhesion-Stiffening Self-Adaptive Soft Robotic Gripper
This article introduces the electroadhesion-stiffening self-adaptive soft robotic gripper (EA-SoGripper), a novel solution to the limitations of traditional rigid robotic grippers. The EA-SoGripper leverages electroadhesion (EA) clutches to dynamically adjust the tension of films, enabling adaptive grasping for objects of varying shapes, sizes, weights, and stiffness. By controlling the applied voltage, the gripper achieves tunable grasping stiffness, with a range of 0.06–1.25 N/mm. A mathematical model predicting load capacity as a function of stiffness and input voltage offers theoretical guidance for practical applications. The gripper integrates a real-time force sensor and a feedback control algorithm, achieving grasping force regulation with high precision. A portable, low-cost ($130), and lightweight (197 g) ac high-voltage power supply system, with a fast response time of 75 ms, further enhances its versatility. Experimental validation demonstrates the EA-SoGripper's ability to securely grasp objects with diverse geometries, including fragile and delicate items, while adapting stiffness to support up to 400 g loads. These results highlight the gripper's potential for applications requiring precise and adaptive handling.
Authors
- Xuanyi Zhou (ORCID: https://orcid.org/0009-0000-8013-8242)
- Xianglong Li (ORCID: https://orcid.org/0000-0001-6208-2580)
- Quan Xiong (ORCID: https://orcid.org/0000-0003-3097-3674)
- Yanhe Zhu (ORCID: https://orcid.org/0000-0002-1960-6278)
- Chen‐Hua Yeow (ORCID: https://orcid.org/0000-0002-6210-4548)
- Haotian Ju (ORCID: https://orcid.org/0000-0001-7911-8324)
- Lina Liu (ORCID: https://orcid.org/0000-0002-5511-2945)
- Dannuo Li (ORCID: https://orcid.org/0009-0005-3928-8974)
Institutions
- National University of Singapore (SG)
- Harbin Institute of Technology (CN)
Publication Details
- Journal
- IEEE/ASME Transactions on Mechatronics
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1109/tmech.2025.3561199
- Citations
- 1
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- National Natural Science Foundation of China