摘要
针对角度法在滤除反向重力加速度过程中数据误差导致的线性加速精度不高的问题,提出一种分段双向去除反向重力加速度算法.首先提出一种基于静止点的数据分段法,将静止点作为端点将运动数据分段,以避免角速度积分过程中误差的段间积累;然后设计一种改进于角度法的双向角度法,以数据段为单位去除反向重力加速度,减小了由段内角速度积分过程带来的积累误差对线性加速度结果精度的影响.使用集成三轴加速度传感器和三轴陀螺仪的六轴传感器,搭配微型电脑树莓派,在不同量程下制作2个数据集;并在2个数据集上进行不同算法的精确度对比实验.结果表明,该算法比角度法获取的线性加速度更精确.
In the process of using angle method to remove the reverse gravitational acceleration, data error can result in low accuracy of linear acceleration. To address this problem, a bi-directional removal of the reverse gravitational acceleration method based on data segmentation is proposed. Firstly, a data segmentation method based on stationary points is designed. The stationary points are used as the endpoint to segment the motion data to avoid inter-segmentation accumulation of error in the angular velocity integration process.Then, a bi-directional angle method improved by the angle method is developed. The reverse gravitational acceleration is removed in units of data segmentations. The accumulation error was generated in the angular velocity integration process. The influence of the accumulated error on the accuracy of linear acceleration is reduced by the bi-directional angle method. Using the Raspberry Pi with the six-axis sensor integrated by a three-axis accelerometer and a three-axis gyroscope, two data sets are made in different ranges. Accuracy comparison experiments of different algorithm are conducted on two sets. The experimental results show the effectiveness and superiority of the proposed method.
作者
李兴
侯振杰
梁久祯
常兴治
Li Xing;Hou Zhenjie;Liang Jiuzhen;Chang Xingzhi(College of Information Science and Engineering, Changzhou University, Changzhou 213164;Jiangsu Province Networking and Mobile Internet Technology Engineering Key Laboratory, Huaian 223003;Changzhou Key Laboratory of Large Plastic Parts Intelligence, Changzhou College of Information Technology, Changzhou 213164)
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2019年第4期560-572,共13页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(61063021)
江苏省产学研前瞻性联合研究项目(BY2015027-12)
江苏省物联网移动互联技术工程重点实验室开放课题(JSWLW-2017-013)
关键词
反向重力加速度
积累误差
静止点
数据分段
reverse gravitational acceleration
accumulation error
stationary points
data segmentation
