基于卡尔曼滤波的无人采矿设备状态预测研究

摘要

In order to make predictions more accurate about the position of the unmanned mining equipment and track the states of it in real time, a prediction method of the position of autonomous mining vehicle based on Kalman filter in the laser positioning and navigation system is proposed. To verify the feasibility, we make up a simple positioning system in our laboratory and carry out verification experiment within this system. The system uses a turntable which can horizontally rotate and tilt as the location tracking base station, two-dimensional motion plat-form which can play translational and vertical movement as the moving target ( actual moving target is one kind of the unmanned mining vehicles) . It applies Kalman filter technology to do filtering and prediction with the coordi-nate information of the moving target, uses the predicted value as the set value of the tracking parameter of the turn-table, so as to make the Laser emitted from the base station steadily and accurately track the moving target.%为了对井下无人采矿设备的状态进行更准确的预测，及时对设备状态进行跟踪，提出了一种激光定位导航系统中的基于卡尔曼滤波的位置预测方法，并在一套试验系统上进行了可行性验证。该系统用可水平旋转、可俯仰的转台作为定位跟踪基站，用可平动和竖直运动的二维运动平台模拟运动目标，采用卡尔曼滤波技术对观测到的运动目标的坐标信息进行滤波和预测，预测值作为转台跟踪的设定值，使基站发出的激光束能平稳准确地跟踪运动目标。