MagicGripper: a mini-magictac integrated gripper enabling multimodal perception in contact-rich manipulation
File(s)
Accepted version
Author(s)
Fan, Wen
Li, Haoran
Cong, Qingzheng
Zhang, Dandan
Type
Journal Article
Abstract
Contact-rich robotic manipulation in unstructured environments demands reliable multimodal perception. Here, we present MagicGripper, a multimodal robotic gripper built around mini-MagicTac, a compact variant of the MagicTac sensor. Mini-MagicTac embeds multi-layer grid structures in a 3D-printed elastomer, enabling visual, proximity, and tactile sensing in a gripper-compatible form factor. In this paper, we introduce the design and multimodal perception capabilities of mini-MagicTac, as well as two algorithmic frameworks for proximity and contact detection. Experimental evaluations show that mini-MagicTac achieves high spatial resolution, accurate contact localisation, and robust force estimation under mechanical and manufacturing variations. Autonomous grasping trials further validate MagicGripper’s reliable multimodal perception and adaptability to complex manipulation scenarios. These results demonstrate MagicGripper as a compact and versatile platform for embodied intelligence in contact-rich environments.
Date Issued
2025-11-11
Date Acceptance
2025-11-01
Citation
IEEE Transactions on Automation Science and Engineering, 2025, 22, pp.24311-24332
ISSN
1545-5955
Publisher
Institute of Electrical and Electronics Engineers
Start Page
24311
End Page
24332
Journal / Book Title
IEEE Transactions on Automation Science and Engineering
Volume
22
Copyright Statement
Copyright © 2025 IEEE. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Publication Status
Published
Date Publish Online
2025-11-11