摘要
水下机器人的传感器信号受环境影响较大，数据滤波一直是机器人控制的核心问题之一。该文在卡尔曼滤波的基础上，引入遗传算法，对卡尔曼滤波方法进行改进，提出基于遗传算法优化的卡尔曼滤波器模型，从而提高水下机器人测量数据的精度．降低系统噪声和量测噪声所带来的误差。OUTLAND1000水下机器人罗经传感器的水池仿真试验结果表明所提改进滤波方法有效、实用。
The sensor signal of UV （underwater vehicles） is seriously affected by environment. Data faltering is one of important problems of UV control. In this paper, a Kalman filter model based on GA （genetic algorithm） is proposed, and the filtering precision of underwater vehicle measurements is improved, and the measurement noise can be reduced, This filtering method is proved to be effective by pool simulation test for Gyro Sensor of OUTLAND1000 underwater vehicles.
作者
胡维莉
王翠翠
刘静
HU Wei-li, WANG Cui-cui, LIU Jing （Laboratory of Underwater Vehicles and Intelligent Systems, Shanghai Maritime University, Shanghai 200135, China）
出处
《电脑知识与技术》
2009年第7期5222-5224,共3页
Computer Knowledge and Technology
基金
上海市教委项目（2008095）
上海市晨光计划（2008CG55）
