巡检机器人全球定位系统/里程计组合定位方法

摘要：针对巡检机器人在校园环境中工作时，GPS信号易受树荫及较高建筑物遮挡而出现定位不准确的问题，提出GPS和ODO组合定位方法。该方法以GPS坐标信息为初始位置，里程计信息为主导航，GPS接收机的脉冲信号作为实时修正数据，利用卡尔曼滤波算法对系统状态进行最优估计，得到较为准确的状态估计值，最后利用状态估计值去修正系统的导航误差。同时在实验平台上进行验证仿真，实验结果表明，机器人以150cm/s的速度行驶80s后其轨迹误差能控制在5cm以内，得出利用多传感器融合技术可以提高机器人的定位精度和可靠性的结论，即通过对GPS和ODO组合定位方法能够有效提高机器人实时定位精度。

Research on GPS/ODO Combined Positioning Method for Inspection Robot

Abstract: Aiming at the problem of inaccurate positioning of GPS signals when patrol robots work in campus environment, which are easily blocked by trees and high buildings, a combined positioning method of GPS and ODO is proposed. This method takes GPS coordinate information as initial position, odometer information as main navigation, pulse signal of GPS receiver as real-time correction data, using Kalman filter algorithm to optimize the state estimation of the system, obtaining more accurate state estimation value, and finally uses state estimation value to correct the navigation error of the system. At the same time, validation and simulation are carried out on the experimental platform. The experimental results show that the trajectory error of the robot can be controlled within 5 cm after it travels at 150 cm/s speed for 80 seconds. It is concluded that the positioning accuracy and reliability of the robot can be improved by using multi-sensor fusion technology. That is to say, the positioning method combined with GPS and ODO can effectively improve the positioning accuracy and reliability of the robot.