摘要
针对水下机器人作业过程中使用扩展卡尔曼滤波算法进行姿态融合解算时,姿态信息会产生较大误差,设计了一种精准进行姿态融合的改进扩展卡尔曼滤波算法。水下机器人导航系统设计的关键在于多传感器数据融合的精确性。为了有效设计水下机器人多传感器数据融合算法,对水下机器人扩展卡尔曼滤波算法进行分析,设计了基于四元数的改进扩展卡尔曼滤波算法进行姿态融合解算。研究表明,改进后的算法降低了数据融合的噪声,提高了系统的收敛性。
Since the large errors will be produced in attitude information when the extended Kalman filter algorithm is used to solve the attitude fusion during the operation of the underwater robot,an improved extended Kalman filter algorithm for precise attitude fusion is designed.The key to the design of the precise navigation system of the underwater robot is the accuracy of the multi-sensor data fusion.In order to effectively design the multi-sensor data fusion algorithm of the underwater robot,the extended Kalman filter algorithm of underwater robot is analyzed and an extended Kalman attitude fusion algorithm based on quaternion is designed to solve the attitude fusion.The experiment shows that the improved extended Kalman algorithm reduces the noise of data fusion and improves the convergence of the system.
作者
朱明明
辛绍杰(指导)
邓寅喆
ZHU Mingming;XIN Shaojie;DENG Yinzhe(School of Mechanical Engineering,Shanghai Dianji University,Shanghai 201306,China)
出处
《上海电机学院学报》
2021年第4期228-233,共6页
Journal of Shanghai Dianji University
基金
上海市高原学科-机械工程项目资助(A1-5701-18-007-08)。
关键词
水下机器人
姿态融合算法
改进扩展卡尔曼滤波算法
underwater robot
attitude fusion algorithm
improved extended Kalman filter algorithm
