This article proposes a method to diminish the pose (position plus attitude) drift experienced by an SVO (Semi-Direct Visual Odometry) based visual navigation system installed onboard a UAV (Unmanned Air Vehicle) by supplementing its pose estimation non linear optimizations with priors based on the outputs of a GNSS (Global Navigation Satellite System) Denied inertial navigation system. The method is inspired in a PI (Proportional Integral) control system, in which the attitude, altitude, and rate of climb inertial outputs act as targets to ensure that the visual estimations do not deviate far from their inertial counterparts. The resulting IA-VNS (Inertially Assisted Visual Navigation System) achieves major reductions in the horizontal position drift inherent to the GNSS-Denied navigation of autonomous fixed wing low SWaP (Size, Weight, and Power) UAVs. Additionally, the IA-VNS can be considered as a virtual incremental position (ground velocity) sensor capable of providing observations to the inertial filter. Stochastic high fidelity Monte Carlo simulations of two representative scenarios involving the loss of GNSS signals are employed to evaluate the results and to analyze their sensitivity to the terrain type overflown by the aircraft as well as to the quality of the onboard sensors on which the priors are based. The author releases the C ++ implementation of both the navigation algorithms and the high fidelity simulation as open-source software.
翻译:本条建议采用一种方法来减少在无人驾驶航空器上安装的基于SVO(Semi-Direct Ovision Odorism)的视觉导航系统所经历的外形(位置加姿态)漂移,办法是根据全球导航卫星系统(全球导航卫星系统)的输出结果,用前期的预估来补充非线性优化,减少在无人惯性惯性导航系统上安装的基于SVO(Semi-Direct 视觉观测仪)的视觉导航系统所经历的外形(位置加姿态)漂移;该方法的灵感来自PI(PI(Proportal Integral综合)控制系统,其中姿态、高度和爬升惯性输出速度作为目标,以确保视觉估计不会偏离其惯性对惯性对等的偏差。 由此产生的IA-VNS(Interliformal Developmental SWAP(Siz, Weight, 和Power)的自动固定翼低惯性导航系统(SWAVA)导航系统(S)的高级导航系统(Sized,Wight,Wight,WI-VNS系统)的高级导航系统(SLA-VNS系统)的高级导航系统)的高度偏移位)的横向位置定位定位,是用于对前一级和高精度对飞行器的高级导航和高级导航的导航系统对高空空空空空空空压的导航结果的分析。