zoukankan      html  css  js  c++  java
  • 泡泡一分钟:Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter

    张宁 Robust Attitude Estimation Using an Adaptive Unscented Kalman Filter

    使用自适应无味卡尔曼滤波器进行姿态估计
    链接:https://pan.baidu.com/s/1TNeRUK84APiwNv1uyQfhHg
    提取码:pbdt

    This paper presents the robust Adaptive unscented Kalman filter (RAUKF) for attitude estimation. Since the proposed algorithm represents attitude as a unit quaternion, all basic tools used, including the standard UKF, are adapted to the unit quaternion algebra. Additionally, the algorithm adopts an outlier detector algorithm to identify abrupt changes in the UKF innovation and an adaptive strategy based on covariance matching to tune the measurement covariance matrix online. Adaptation and outlier detection make the proposed algorithm robust to fast and slow perturbations such as magnetic field interference and linear accelerations. Experimental results with a manipulator robot suggest that our method overcomes other algorithms found in the literature.

    本文介绍了用于姿态估计的鲁棒自适应无味卡尔曼滤波器(RAUKF)。由于所提出的算法将姿态表示为单位四元数,因此所使用的所有基本工具(包括标准UKF)都适用于单位四元数代数。此外,该算法采用离群值检测器算法来识别UKF创新中的突变,并采用基于协方差匹配的自适应策略在线调整测量协方差矩阵。自适应和离群值检测使所提出的算法对诸如磁场干扰和线性加速度之类的快速和慢速扰动具有鲁棒性。 机械手机器人的实验结果表明,我们的方法优于文献中发现的其他算法。

  • 相关阅读:
    linux转换win下乱码txt命令
    linux下vi命令大全详细版本
    ubuntu系统如何安装adb调试环境
    LeetCode136---只出现一次的数字
    微信发朋友圈--用例设计(转)
    微服务
    LeetCode1---两数之和
    python输出
    爬楼梯,N级楼梯有多少种走法?
    list数组排序---stream
  • 原文地址:https://www.cnblogs.com/feifanrensheng/p/11830803.html
Copyright © 2011-2022 走看看