摘要
文章针对智能车或无人机等需要姿态解算的产品在外界环境可视性差,不支持视觉定位,或仅仅物体内部的单个模块需要姿势解算及无法安装摄像头或不可安装摄像头的问题,为更精准有效率获取姿态,做出了相对应的算法设计。针对智能车,该项目主张靠硬件传感器通过算法获取姿态,达到小车控制的目的,使小车行驶更加稳定。采用了卡尔曼滤波算法,完成了对加速度计的信号滤波和对陀螺仪的滤波。做到初始数据真实、稳定。初始数据采用四元数法进行解算。获得小车的姿态角,将加速度计与陀螺仪姿态解算融合,得到精确小车姿态,实现小车在不同环境下的精准控制。
This paper proposes an algorithm design for products that require attitude calculation,such as intelligent cars or drones,when the external environment has poor visibility,visual positioning is not supported,or only a single module inside the object requires attitude calculation and a camera cannot be installed or is not installable.The proposed project advocates relying on hardware sensors to obtain attitude through algorithms,to achieve the purpose of controlling the car and make the car run more stable.By utilizing the Kalman filter algorithm,the accelerometer and gyroscope signals are effectively filtered,thus guar-anteeing the precision and stability of the original data.The quaternion method is used to calculate the initial data and obtain the attitude angle of the car.The attitude calculation of the accelerometer and gyroscope is fused to obtain the accurate attitude of the car and achieve precise control of the car in different environments.
作者
万喆聪
曾启渊
詹春
WAN Zhecong;ZENG Qiyuan;ZHAN Chun(Jiangxi Science and Technology Normal University,School of Communication and Electronics,Nan Chang 330000,China)
出处
《长江信息通信》
2023年第8期104-108,共5页
Changjiang Information & Communications
基金
国家级大学生创新训练项目(202211318021)
