Dipartimento di Ingegneria dell'Informazione (DINFO), Università di Firenze, via di Santa Marta 3, 50139 Firenze, Italy.
Dipartimento di Fisica e Astronomia & LENS, Università di Firenze, via G. Sansone 1, 50019 Sesto Fiorentino, Italy.
Sensors (Basel). 2021 Jan 8;21(2):391. doi: 10.3390/s21020391.
In this paper, solutions for precise maneuvering of an autonomous small (e.g., 350-class) Unmanned Aerial Vehicles (UAVs) are designed and implemented from smart modifications of non expensive mass market technologies. The considered class of vehicles suffers from light load, and, therefore, only a limited amount of sensors and computing devices can be installed on-board. Then, to make the prototype capable of moving autonomously along a fixed trajectory, a "cyber-pilot", able on demand to replace the human operator, has been implemented on an embedded control board. This cyber-pilot overrides the commands thanks to a custom hardware signal mixer. The drone is able to localize itself in the environment without ground assistance by using a camera possibly mounted on a 3 Degrees Of Freedom (DOF) gimbal suspension. A computer vision system elaborates the video stream pointing out land markers with known absolute position and orientation. This information is fused with accelerations from a 6-DOF Inertial Measurement Unit (IMU) to generate a "virtual sensor" which provides refined estimates of the pose, the absolute position, the speed and the angular velocities of the drone. Due to the importance of this sensor, several fusion strategies have been investigated. The resulting data are, finally, fed to a control algorithm featuring a number of uncoupled digital PID controllers which work to bring to zero the displacement from the desired trajectory.
本文针对小型(例如 350 级)自主无人机(UAV)的精确机动问题,设计并实现了从智能修改非昂贵的大众市场技术的解决方案。所考虑的车辆类别负载较轻,因此只能在机载设备上安装有限数量的传感器和计算设备。然后,为了使原型能够沿着固定轨迹自主移动,在嵌入式控制板上实现了一个“网络飞行员”,能够根据需要替代人类操作员。这个网络飞行员通过定制的硬件信号混合器来覆盖命令。无人机可以通过使用可能安装在 3 自由度(DOF)万向架悬架上的摄像头来定位自己在环境中,而无需地面协助。计算机视觉系统处理视频流,用已知的绝对位置和方向来标记地标。该信息与来自 6 自由度惯性测量单元(IMU)的加速度融合,以生成“虚拟传感器”,为无人机的姿态、绝对位置、速度和角速度提供精确估计。由于该传感器的重要性,研究了几种融合策略。最后,将生成的数据输入到一个控制算法中,该算法具有多个解耦的数字 PID 控制器,这些控制器的工作是将与期望轨迹的位移归零。