基于SLAM的旋翼无人机组合导航算法研究

Research on Integrated Navigation Algorithm of Rotor UAV Based on SLAM

摘要:

在旋翼无人机组合导航中，针对缺乏GPS作为导航信号源的室内飞行环境，为了达到精确定位的目的，提出一种基于SLAM（simultaneous localization and mapping）的旋翼无人机组合导航算法。首先，引入双线性插值算法，实现基于扫描匹配的即时定位与地图构建；其次，对陀螺仪、加速度计和磁罗盘建立捷联惯导系统误差模型，针对旋翼无人机的使用环境对误差模型进行简化；最后，应用联邦卡尔曼滤波算法，设计组合导航系统模型，将SLAM算法和捷联惯导系统估计出的位置数据进行融合。仿真结果表明所设计基于SLAM的旋翼无人机组合导航算法能够进一步提高组合导航系统对旋翼无人机位姿估计的精度。

Abstract:

In the research of of rotorcraft UAV, in order to improve the positioning accuracy in the lack of GPS environment, a SLAM-based integrated navigation algorithm for rotorcraft is proposed in the paper. Firstly, completing SLAM process based on scan matching algorithm by introducing bilinear interpolation algorithm. Then, establishing the strapdown inertial navigation system error model, and simplifying the error model for the use environment of the rotor UAV. Finally, the Federated Kalman filter algorithm is designed to fuse the SLAM algorithm with the data output by the strapdown inertial navigation system. The simulation results show that the accuracy of position estimation and attitude estimation is improved by using the SLAM-based integrated navigation algorithm.