基于磁-惯性传感融合的灵巧手指单元全姿态信息反演方法

doi:10.3901/JME.2022.18.133

机械工程学报 ›› 2022, Vol. 58 ›› Issue (18): 133-140.doi: 10.3901/JME.2022.18.133

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基于磁-惯性传感融合的灵巧手指单元全姿态信息反演方法

申慧敏¹, 葛瑞康¹, 顾晓伟¹, 蔡晓童¹, 甘屹¹, 杨赓²

1. 上海理工大学机械工程学院上海 200093;
2. 浙江大学流体动力与机电系统国家重点实验室杭州 310027

收稿日期:2021-10-28 修回日期:2022-03-06 出版日期:2022-09-20 发布日期:2022-12-08
通讯作者: 杨赓(通信作者)，男，1980年出生，博士，研究员，博士研究生导师。主要研究方向为智能机器人及人-机交互技术。E-mail：yanggeng@zju.edu.cn
作者简介:申慧敏,女,1987年出生,博士,副教授。主要研究方向为人-机交互技术技术及电磁检测技术;E-mail:hmshen@usst.edu.cn
基金资助:
国家自然科学基金(52175055，51975513)、浙江省基础青年基金 (LR20E050003)和宁波科技创新2025重大专项(2020Z022)资助项目。

Method of Dexterous Finger Unit Full-pose Modeling Based on Magnetic-inertial Sensor Fusion

SHEN Huimin¹, GE Ruikang¹, GU Xiaowei¹, CAI Xiaotong¹, GAN Yi¹, YANG Geng²

1. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093;
2. State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027

Received:2021-10-28 Revised:2022-03-06 Online:2022-09-20 Published:2022-12-08

摘要/Abstract

摘要： 作为人类与外界环境互动的重要自然媒介，手具有高度的灵活性和复杂性，高效准确的手部动作和姿态识别对实现基于手部的人-机-环境共融具有重要意义。针对手部显著的个体差异特性，提出基于磁-惯性传感信息融合技术的个性化手指单元参数化模型构建方法，为实现精准的人-机-环境感知和共融提供技术支持。结合手部的指骨生物构造约束，建立手指单元运动学模型；通过结构化磁场标记技术，搭建磁-惯性信息融合的手指单元全姿态反演系统，完成个性化手指单元参数化模型构建。通过对不同志愿者手指单元开展连续路径对比试验以及单点定位精度验证试验，证明提出的基于磁-惯性传感信息融合技术的个性化手指单元全姿态信息反演方法定位精度分布在[1.43, 2.81] mm。

关键词: 灵巧手, 手指单元, 磁-惯性传感, 信息融合, 全姿态反演

Abstract: As an important natural medium for human-environment-interaction, human hand takes advantages of high degrees of flexibility and complexity, and efficient and accurate hand motion and gesture recognition is of great significance for realizing hand-based human-machine-environment integration. A method for constructing a personalized dexterous finger unit full-pose information based on the magnetic-inertial sensor information fusion technology is proposed, in order to provide technical support for accurate human-machine-environment perception and inclusiveness. Combined with the biological structural constraints of the phalanx of the hand, a finger unit kinematics model was established. Through the structured magnetic field marking technology, a magnetic-inertial information fusion finger unit full-pose deriving system is developed, and the construction of a personal parameterized finger unit model is completed. The continuous path comparison test and single-point positioning accuracy verification test of different volunteer finger units proved that the proposed method for personalized finger unit full-pose information derivation based on magnetic-inertial sensor information fusion technology can achieve a positioning accuracy between [1.43, 2.81] mm.

Key words: dexterous hand, finger unit, magnetic-inertial sensing, information fusion, full-pose inversion

中图分类号:

TP241

申慧敏, 葛瑞康, 顾晓伟, 蔡晓童, 甘屹, 杨赓. 基于磁-惯性传感融合的灵巧手指单元全姿态信息反演方法[J]. 机械工程学报, 2022, 58(18): 133-140.

SHEN Huimin, GE Ruikang, GU Xiaowei, CAI Xiaotong, GAN Yi, YANG Geng. Method of Dexterous Finger Unit Full-pose Modeling Based on Magnetic-inertial Sensor Fusion[J]. Journal of Mechanical Engineering, 2022, 58(18): 133-140.

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基于磁-惯性传感融合的灵巧手指单元全姿态信息反演方法

Method of Dexterous Finger Unit Full-pose Modeling Based on Magnetic-inertial Sensor Fusion

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