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A New MEMS Gyro North Finding Approach Using LSM for Mobile Robot Heading Detection

机译:一种新的MEMS Gyro North发现方法,使用LSM移动机器人航向检测

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摘要

In this paper, we present a new approach for mobile robot heading detection using MEMS Gyro north finding method. Based on this, the robot heading angle measurement scheme is proposed; improved north finding theory and algorithm are also explained. Several approaches are applied to confirm system's precision and effectiveness. In order to find out the heading angle, we use a single axis MEMS gyroscope and accelerometer package to sense the angle between the robot heading direction and the north. At the same time, we apply the accelerometer to sense the effect of the earth gravity to ensure the targeting function on both horizontal road and rugged road. To reach enough estimation accuracy and reduce detection time, we apply Least Square Method (LSM) and Extended Kalman Filter (EKF) for the signal fitting, filtering and data fusion. Through a turn-table, we setup a carouse ling system to decrease the substantial bias effect on gyroscope's heading angle. For the evaluation of the proposed method, this system is implemented to the Pioneer robot platform. The performance and heading error are analyzed after the test. From the simulation and experimental results, system's accuracy, usefulness and adaptability are shown.
机译:在本文中,我们使用MEMS Gyro Northing方法提出了一种新的移动机器人航向检测方法。基于此,提出了机器人标题角度测量方案;还解释了北北发现理论和算法。采用几种方法来确认系统的精确度和有效性。为了找出标题角度,我们使用单轴MEMS陀螺仪和加速度计封装来感测机器人标题方向与北方之间的角度。与此同时,我们应用加速度计以检测地球重力的效果,以确保水平道路和崎岖的道路上的瞄准功能。为了达到足够的估计精度并降低检测时间,我们应用最小二乘法(LSM)和扩展卡尔曼滤波器(EKF),用于信号拟合,过滤和数据融合。通过旋转桌,我们设置了一台卡特玲系统,以降低陀螺仪的出头角度的大幅偏差影响。为了评估所提出的方法,该系统用于先驱机器人平台。在测试后分析性能和标题误差。从模拟和实验结果来看,系统的准确性,有用和适应性。

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