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Miniaturized 3D Magnetic Force Sensor via Laser-Assisted Folding and Magnetization for Enhanced Robotic Dexterity
Yujie Huang1,2, Huangzhe Dai1,2, Chengqian Zhang1,2
1State Key Laboratory of Fluid Power and Mechatronic Systems, College of Mechanical Engineering, Zhejiang University, Hangzhou, China.
Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|March 27, 2026
Summary
A new laser-assisted folding and magnetization method enables highly accurate, miniaturized magnetic tactile sensors. These sensors improve robotic dexterity by providing efficient 3D force decoupling for tasks like adaptive grasping and material stiffness recognition.
Area of Science:
- Robotics
- Materials Science
- Sensor Technology
Background:
- Miniaturized magnetic tactile sensors are crucial for enhancing robotic dexterity and perception.
- Fabricating precise planar magnetic structures for miniaturized sensors presents significant challenges.
Purpose of the Study:
- To develop a novel method for creating miniaturized, centripetally magnetized films for tactile sensing.
- To demonstrate the capability of these sensors in achieving efficient 3D force decoupling.
Main Methods:
- Introduced a laser-assisted folding and magnetization (LAFM) technique utilizing laser-etched grooves for controlled film folding.
- Achieved accurate magnetization alignment in films as small as 5 × 5 mm2.
- Verified magnetic field accuracy with root mean square errors (RMSEs) below 5 µT.
Main Results:
- Developed compact 3D force sensors with high force resolution (tangential 3 mN, normal 9 mN) and rapid response (34 ms).
- Demonstrated long-term stability exceeding 2500 cycles with less than 1% deviation.
- Successfully integrated sensors onto a mobile manipulator for adaptive grasping and onto a dexterous hand for non-destructive stiffness recognition.
Conclusions:
- The LAFM method provides a robust pathway for fabricating miniaturized tactile sensors.
- These sensors significantly advance robotic perception, embodied intelligence, and manipulation capabilities.
- The technology enables adaptive grasping, obstacle traversal, and material property recognition in robots.
