...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Mechanical systems and signal processing >A fusion strategy for reliable attitude measurement using MEMS gyroscope and camera during discontinuous vision observations
【24h】

A fusion strategy for reliable attitude measurement using MEMS gyroscope and camera during discontinuous vision observations

机译：在不连续视觉观测期间使用MEMS陀螺仪和相机可靠姿态测量的融合策略

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

For indoor close-range high-accuracy attitude measurement using inertial and vision sensors, the major challenge is to achieve a reliable attitude in various scenarios, specifically in the absence of vision information. To address this challenge, we present a fusion strategy for reliable attitude measurement using a micro electro mechanical system (MEMS) gyroscope and camera, particularly during discontinuous vision observations. The proposed algorithm consecutively executes update and prediction modes. In the update mode, when both inertial and visual data are available, the complete Kalman Filter (KF) conducts the entire filtering process and updates residual and state errors. In the absence of visual data, the partial KF operates only when the time update and filtering state vectors are compensated by the transfer residual, which is estimated through self-propagating state error. The parameters of least-squares support vector machine (LSSVM-NARX) continuously update until the next discontinuous vision observation occurs, with the desired outputs and inner inputs being the error angles and the exogenous inputs being the gyroscope values and time. In the prediction mode, without visual data, LSSVM-NARX can provide estimated angle errors between the complete and partial KFs, which are used to eliminate errors from partial KF output vectors to obtain a reliable and accurate attitude solution. Comparisons and extensive semi-physical simulation experiments under various motion trajectories were performed to validate the effectiveness and superiority of the proposed scheme in an accurate and reliable attitude measurement capability associated with discontinuous observations.
机译：对于使用惯性和视觉传感器的室内近距离的高精度姿态测量，主要挑战是在各种场景中实现可靠的态度，特别是在没有视觉信息的情况下。为了解决这一挑战，我们展示了一种使用微机械系统（MEMS）陀螺仪和相机的可靠姿态测量的融合策略，特别是在不连续视觉观测期间。所提出的算法连续执行更新和预测模式。在更新模式中，当惯性和视觉数据都有可用时，完整的卡尔曼滤波器（KF）进行整个过滤过程并更新残差和状态错误。在没有视觉数据的情况下，局部KF仅在时间更新和过滤状态向量通过传输残差补偿时操作，这通过自传状态误差估计。最小二乘支持向量机（LSSVM-NARX）的参数连续更新，直到发生下一个不连续视觉观察，所需的输出和内输入是误差角，外源输入是陀螺值和时间。在预测模式中，没有视觉数据，LSSVM-NARX可以在完整和部分KF之间提供估计的角度误差，其用于消除部分KF输出矢量的错误以获得可靠且准确的姿态解决方案。在各种运动轨迹下进行比较和广泛的半物理模拟实验，以验证提出方案的效力和优越性，以与不连续观察相关的准确且可靠的姿态测量能力。

著录项

  • 来源
    《Mechanical systems and signal processing》 |2021年第8期|107772.1-107772.17|共17页
  • 作者

    Xiao-ting Guo; Chong Shen; Jun Tang; Jie Li; Jun Liu;

  • 作者单位

    Key Laboratory of Instrumentation Science & Dynamic Measurement Ministry of Education School of Instrument and Electronics North University of China Taiyuan 030051 PR China;

    Key Laboratory of Instrumentation Science & Dynamic Measurement Ministry of Education School of Instrument and Electronics North University of China Taiyuan 030051 PR China;

    Key Laboratory of Instrumentation Science & Dynamic Measurement Ministry of Education School of Instrument and Electronics North University of China Taiyuan 030051 PR China;

    Key Laboratory of Instrumentation Science & Dynamic Measurement Ministry of Education School of Instrument and Electronics North University of China Taiyuan 030051 PR China;

    Key Laboratory of Instrumentation Science & Dynamic Measurement Ministry of Education School of Instrument and Electronics North University of China Taiyuan 030051 PR China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Attitude measurement; Data fusion; Transfer residual correction; LSSVM; NARX;

    机译：态度测量;数据融合;转移剩余校正;LSSVM;鼻子;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号