The flapping-wing aerial vehicle (FWAV) is a new type of flying robot that mimics the flight mode of birds and insects. However, FWAVs have their special characteristics of less load capacity and short endurance time, so that most existing systems of ground target localization are not suitable for them. In this paper, a vision-based target localization algorithm is proposed for FWAVs based on a generic camera model. Since sensors exist measurement error and the camera exists jitter and motion blur during flight, Gaussian noises are introduced in the simulation experiment, and then a first-order low-pass filter is used to stabilize the localization values. Moreover, in order to verify the feasibility and accuracy of the target localization algorithm, we design a set of simulation experiments where various noises are added. From the simulation results, it is found that the target localization algorithm has a good performance.
翻译:拍风飞行器(FWAV)是一种新型的飞行机器人,模仿鸟类和昆虫的飞行模式,然而,FWAV具有较低的载荷容量和短耐力时间的特殊性,因此大多数现有的地面目标定位系统不适合它们。在本文中,基于通用相机模型,为FWAV提出了基于视觉的目标定位算法。由于传感器存在测量错误,而且相机在飞行期间是虚弱和模糊的,因此在模拟实验中引入了高斯噪音,然后使用了第一级低射线过滤器来稳定定位值。此外,为了核实目标本地化算法的可行性和准确性,我们设计了一套模拟实验,其中添加了各种噪音。根据模拟结果,发现目标本地化算法具有良好的性能。