定位建图是智能车自动导航的关键问题之一。以未知环境为研究背景, 研究基于二维激光雷达的定位建图系统。激光雷达扫描周边环境建图, 里程计和IMU完成航位推算提供位姿, 通过滤波匹配不断更新地图构建全局地图。为实现精确实时的定位建图, 分析了飞行时间法激光雷达测距误差和基于IMU和里程计的航位推算误差, 通过线性最小二乘和加权移动平均滤波对激光雷达原始数据进行标定和滤波;通过互补滤波抑制陀螺仪低频噪声和磁力计高频噪声;在所搭建的基于激光雷达的定位建图系统上进行了实验。实验结果表明, 经过滤波校正后, 提高了系统定位建图精度和稳定性。

Positioning and mapping is one of the key issues in the automatic navigation of smart cars. Considering the unknown environment as research background, the positioning and mapping system based on 2D lidar (Light Detection And Ranging) is studied . The lidar scans the surrounding environment to build a map, and continuously update the map through the filter matching to construct a global map with the odometer and IMU which complete the dead reckoning and provide a pose. In order to realize accurate real-time positioning and mapping, the time-of-flight lidar ranging error and the dead reckoning error based on IMU and odometer are analyzed. The lidar raw data is calibrated and filtered by linear least squares and weighted moving average filtering. The gyro low frequency noise and the magnetometer high frequency noise are suppressed by complementary filtering. Experiments were carried out on the built lidar-based positioning and mapping system. The experiment results show that the accuracy and stability of the positioning and mapping are improved after the filter correction.