LIDAR/MEMS IMU integrated navigation (SLAM) method for a small UAV in indoor environments
LIDAR/MEMS IMU integrated navigation (SLAM) method for a small UAV in indoor environments
复制标题
DOI：
10.1109/inertialsensors.2014.7049479
复制
发表时间：
2014-09
期刊：
影响因子：
--
通讯作者：
Rongbing Li;Jianye Liu;Ling Zhang;Y. Hang
中科院分区：
文献类型：
--
作者：
Rongbing Li;Jianye Liu;Ling Zhang;Y. Hang
基于LIDAR和MEMS IMU的同步定位与测绘(SLAM)是一种自主组合导航技术。它可以在GNSS中断时提供小型无人机在室内框架内的姿态、速度位置。提出了一种综合激光雷达和微电子机械系统IMU测量数据的方法。激光雷达测量是一组距离和扫描角度。利用MEMS捷联惯导单元获得的角速率和加速度建立了简化的捷联惯导方程。该方法的第一步是从激光雷达的测量数据中提取环境特征，并构建特征地图。然后，基于MEMS惯导系统的辅助信息和室内环境的结构性假设，建立了姿态机动过程中扫描平面变化引起的激光雷达测量误差模型，并进行了补偿。利用环境特征延迟匹配算法得到的相对位置参数和相邻时刻激光雷达测量值的差异，通过凯曼滤波估计MEMS惯导系统和MEMS传感器的误差。为验证LIDAR/MEMS IMU组合导航系统的实用性，设计了LIDAR/MEMS IMU样机。通过室内实验，验证了LIDAR/MEMS IMU组合导航系统的应用前景。
Simultaneous Localization and Mapping (SLAM) based on LIDAR and MEMS IMU is a kind of autonomous integrated navigation technology. It can provide attitude, velocity position for a small UAV in an indoor frame during the outage of GNSS. A method of integrating the measurements from a LIDAR and a MEMS IMU was proposed in the paper. LIDAR measurements are a set of ranges and scan angles. The angle rates and accelerations from MEMS IMU are used to drive the simplified strapdown INS equations. The first step of the method is environment features extracting from the measurements of LIDAR and constructing a feature map. Then, the model of errors of LIDAR measurement due to the change of the scan plane during the attitude manoeuver is established and compensated based on aiding information from MEMS INS and the assumption about the structural indoor environment. The relative position parameters derived from environmental features delay matching algorithm and the differences of measurements of LIDAR at adjacent times are used to estimate the error of MEMS INS and MEMS sensors by a Kaiman Filter. A LIDAR/MEMS IMU prototype was designed to verify the practicability of the integrated navigation system of LIDAR and MEMS IMU. Some experiments were carried out in a room and the results demonstrated the potential use of the LIDAR/MEMS IMU integration navigation system.