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Model-Aided Navigation with Wind Estimation for Robust Quadrotor Navigation

机译:模型辅助导航,具有强大的Quadrotor导航的风估计

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GPS outages are a central issue for accurate navigation of unmanned aerial vehicles (UAVs) in outdoor environments: The navigation solution of an inertial navigation system (INS) solely relying on measurements from a low-cost MEMS IMU quickly deteriorates and becomes unusable without aiding measurements. Therefore, new approaches are necessary for providing an accurate navigation solution at all times. In this paper, a model-aided navigation system for a quadrotor helicopter is extended by estimating the wind velocity. The main objective is to increase robustness and allow robust operation during all environmental conditions. Moreover, the benefit of this approach is that it does not require additional sensors, such as a camera or a differential GPS module and, therefore, does not increase hardware cost. Simulation results and outdoor test flights show that an accurate wind velocity estimation is obtained in challenging conditions. Even during GPS outages an accurate wind velocity estimation is still possible given that a higher-grade MEMS IMU is used. Moreover, it is shown that position estimation accuracy during GPS outages is significantly improved by including the wind velocity in the model-aided navigation system.
机译:GPS中断是户外环境中无人驾驶飞行器(无人机)的准确导航的核心问题:惯性导航系统(INS)的导航解决方案仅依赖于低成本MEMS IMU的测量速度迅速劣化,并且在没有辅助测量的情况下变得无法使用。因此,新方法是始终提供准确的导航解决方案所必需的。在本文中,通过估计风速来延长用于四轮车直升机的模型辅助导航系统。主要目标是增加鲁棒性并在所有环境条件下允许稳健的操作。此外,这种方法的益处是它不需要额外的传感器,例如相机或差分GPS模块,因此不会增加硬件成本。仿真结果和户外测试飞行表明,在具有挑战性的情况下获得了精确的风速估计。即使在GPS中,也可以给出准确的风速估计,因为使用了更高级MEMS IMU。此外,示出通过包括模型辅助导航系统中的风速,显着改善了GPS中断期间的位置估计精度。

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