摘要
为了更有效、可靠地从传感器原始数据中获取信息,介绍了一种移动机器人同步定位与地图创建的方法。该方法使用二维激光测距传感器实现室内环境中的移动机器人自主定位,依靠无嗅卡尔曼滤波器减少定位过程中所产生的误差;通过激光测距仪采集机器人所在环境数据的曲率函数,将环境特征分解为直线、拐角和曲线三类基本定位特征,并结合环境地图得到机器人位置和姿态的最优解。试验结果表明,该定位方法对于室内环境是有效的。
To obtain the information from the original data more effectively and reliably, the method of synchronous positioning and map creation for mobile robots is introduced. With this method, the 2-D laser range finding sensor is used for autonomous positioning of the robot under indoor environment; and the error caused in positioning procedures are reduced by unscented Kalman filter （ UKF ）. Through collecting the curvature functions of the environmental data by laser range finder, the environmental feature is decomposed into three categories of positioning features, i. e. , straight lines, comers and curves; combining with environmental map, the optimal solution of the position and attitude for robot is obtained. The experimental results indicate that this positioning method is effective for indoor environment.
出处
《自动化仪表》
CAS
北大核心
2012年第7期15-18,共4页
Process Automation Instrumentation
关键词
机器人
定位
激光测距仪
无嗅卡尔曼滤波
计算精度
Robot Positioning Laser range finder Unscented Kalman filter Calculation accuracy
