姿势
多极展开
人工智能
计算机视觉
计算机科学
分辨率(逻辑)
触觉传感器
声学
物理
量子力学
机器人
作者
Jianglong Huang,Yunjiang Lou,Xiaogang Xiong,Xiansheng Yang,Yanjie Li
标识
DOI:10.1109/tim.2024.3522631
摘要
Magnetic tactile sensors are widely used in tactile servo and robotic manipulations because of their compact size and high sensitivity. However, their spatial resolution is constrained by the number of Hall elements in a contact area, while their limited capacity to perceive 3-D information hinders their broader applications. This article introduces a grid multipole magnetization method for magnetic tactile sensors that achieves super-resolution and 3-D pose perception without increasing the density of Hall elements. By magnetizing the soft contact surface with the proposed grid multipole magnetization method and equipping with different deep neural networks (DNNs), this newly fabricated magnetic-based tactile sensor offers improved 3-D sensing capabilities at a sampling frequency of 380 Hz of all five Hall sensors within a compact size of $20 \times 20$ mm and a thickness of 3.5 mm. It accurately perceives single-point contacts (contact force ranging from 0 to 2.5 N, with spatial and force resolutions of 0.1 mm and 0.05 N, respectively), as well as providing measurements for 2-D rotation angles (−90° to 90°, resolution: 0.33°) and capturing 3-D pose features (roll, pitch, and yaw angle resolutions: 0.046°, 0.128°, and 0.096° over ranges from −5° to 5°). The effectiveness of this methodology is validated through experiments demonstrating a remarkable improvement in spatial super-resolution by a factor of 70, offering innovative solutions for robotic tactile sensors with numerous potential applications in dexterous manipulation.
科研通智能强力驱动
Strongly Powered by AbleSci AI