激光SLAM移动机器人室内定位研究

Research on indoor positioning of LiDAR SLAM mobile robot

针对目前室内移动导航定位精度低和累积误差大的问题,提出了一种激光雷达(LiDAR)和惯性测量单元(IMU)相融合的导航定位系统。首先,该方法是从LiDAR扫描测量中提取环境特征和构建地图,然后,由IMU采集的姿态信息通过卡尔曼滤波,补偿由于LiDAR扫描引起的位置和姿态输出的误差,以提高机器人移动的定位精度。试验结果表明,该方法可以提高室内移动机器人定位和构建地图的精度和稳健性。

Aiming at the low accuracy and cumulative error of indoor mobile navigation,a fusion navigation system based on light detection and ranging(LiDAR)and inertial measurement unit(IMU)is proposed.First,the method extracts environmental features and constructs maps from LiDAR scan measurements.Then,the pose information collected by the IMU compensates for the position and attitude output errors caused by LiDAR scans by Kalman filtering to improve the positioning of the robot movement precision.The experimental results show that the method can improve the accuracy and robustness of indoor mobile robot positioning and map construction.