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使用补充波器和卡尔曼波器的IMU/UWB融合方法,用于混合上肢运动估计.

Yutong Shi1, Yongbo Zhang1,2, Zhonghan Li1

  • 1School of Aeronautic Science and Engineering, Beihang University, Beijing 100191, China.

Sensors (Basel, Switzerland)
|August 12, 2023
PubMed
概括

这项研究介绍了一种使用低成本可穿戴传感器的新型混合动力运动跟踪系统. 惯性测量单元 (IMU) 和超宽带 (UWB) 数据的融合显著提高了上肢运动跟踪的准确性.

关键词:
卡尔曼过器可以过.马德威克定向过器的导向过器惯性测量单位 (IMU) 是指惯性测量单位.运动估计运动估计超宽带 (UWB) 是指超宽带.

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科学领域:

  • 人与计算机的交互
  • 航空航天工程 航空航天工程
  • 机器人技术 机器人技术 机器人技术
  • 生物力学 生物力学

背景情况:

  • 光学运动捕捉系统昂贵且对照明敏感.
  • 惯性测量单元 (IMU) 传感器受到漂移的影响.
  • 现有的系统面临成本,环境敏感性和准确性方面的局限性.

研究的目的:

  • 开发一种混合,低成本的运动跟踪系统,用于上肢运动.
  • 为了提高准确性,将IMU和超宽带 (UWB) 传感器的数据合并.
  • 克服航空航天应用中现有的运动捕捉技术的局限性.

主要方法:

  • 提出了一种新的算法,它结合了第四阶Runge-Kutta (RK4) Madgwick补充定向波器和卡尔曼波器.
  • 利用来自惯性测量单元 (IMU) 和超宽带 (UWB) 系统的数据融合.
  • 采用马德威克RK4过器来补偿陀螺仪漂移和卡尔曼过器来融合UWB测量以减少漂移.

主要成果:

  • 拟议的IMU/UWB融合方法显示,与IMU-only方法相比,根平均平方误差 (RMSE) 平均下降1.2厘米.
  • 使用UWB定位实现了无漂移的位置估计,卡尔曼波器与IMU计算的位置合并.
  • 实验结果证实了人类上肢运动跟踪的高可行性和稳定性.

结论:

  • 混合IMU/UWB运动跟踪系统为上肢运动分析提供了具有成本效益和准确的解决方案.
  • 拟议的数据融合算法有效地减轻了传感器漂移,并提高了跟踪精度.
  • 这项技术在航空航天领域及其他领域的人与计算机交互方面的应用具有显著的潜力.