基于视觉延时补偿的无人机室内实时导航系统

UAV INDOOR REAL-TIME NAVIGATION SYSTEM BASED ON VISUAL DELAY COMPENSATION

在无人机视觉辅助惯性导航系统中,不确定延时的图像数据在无人机室内导航中是无法满足与其他传感器同步要求的,因此准确估计视觉传感器与惯性测量单元(IMU)之间的相对延时是非常重要的.本文提出了一种可以有效估计图像延时的方法,并根据延时进行视觉数据的延时补偿,最后利用扩展卡尔曼滤波(EKF)实现IMU数据与视觉数据的融合,从而估计出无人机的实时位姿和速度.通过软件仿真和在无人机平台上的实验验证结果表明,该方法能准确地估计延时,使室内实时导航的定位性能得到明显改善.

In UAV vision-assisted inertial navigation system,the image data with uncertain delay cannot meet the synchronization requirements with other sensors in the UAV indoor navigation.Therefore,the distance between the vision sensor and the inertial measurement unit(IMU)is accurately estimated.Relative delay is very important.This paper proposes a method that can effectively estimate the image delay,and compensate the delay of the visual data according.Finally,it is capable to finally use the extended Kalman filter(EKF)to realize the fusion of the IMU data and the visual data to estimate the UAV Real-time pose and speed.The results of software simulation and experimental verification on the UAV platform demonstrate that the method can accurately estimate the time delay and significantly improve the positioning performance of indoor real-time navigation.