论文标题
由PI启发的惯性先验的自主无人机的GNSS贬低的半直接视觉导航
GNSS-Denied Semi Direct Visual Navigation for Autonomous UAVs Aided by PI-Inspired Inertial Priors
论文作者
论文摘要
本文提出了一种方法，可以减少基于SVO的姿势（位置加上态度）漂移，该方法是由SVO（半导体视觉验光）基于基于的视觉导航系统安装在船上的无人机（无人驾驶飞机车辆）上，通过补充其姿势估计的非线性优化，其基于基于GNSS的输出（全球导航卫星系统的输出）的PRIORS进行了无线性优化。该方法的灵感来自PI（比例积分）控制系统，在该系统中，攀岩惯性输出的态度，高度和速率是确保视觉估计远离其惯性对应物的目标。由此产生的IA-VN（惯性辅助的视觉导航系统）实现了自主固定机翼低交换（尺寸，重量和功率）无人机固有的固有的水平位置漂移。另外，IA-VN可以被视为能够为惯性滤波器提供观测值的虚拟增量位置（地面速度）传感器。使用涉及涉及GNSS信号丢失的两个代表性场景的随机高保真蒙特卡洛模拟，用于评估结果并分析飞机对地形类型的敏感性，以及对先验者所基于的板载传感器的质量。作者释放了导航算法的C ++实现，并将高保真模拟作为开源软件。
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.
