Data Collected with Package Delivery VTOL Drone

This experiment was performed in order to empirically measure the energy use of electric Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicles (UAVs). We autonomously direct a MakeFlyEasy Fighter VTOL drone to take off, carry a range of payload weights on two different flight patterns, and land. Between flights, we varied specified parameters through a set of discrete options, payload of 0 , 400 g and 800 g; altitude during cruise of 50 m and 100 m; and speed during cruise of 18 m/s and 22 m/s. We simultaneously collect data from a broad array of on-board sensors. The onboard sensors used to collect these data are * Wind sensor: FT Technologies FT205 UAV-mountable, pre-calibrated ultrasonic wind sensor with accuracy of ± 0.1 m/s and refresh rate of 10 Hz.; * Position: 3DM-GX5-45 GNSS/INS sensor pack. These sensors use a built-in Kalman filtering system to fuse the GPS and IMU data. The sensor has a maximum output rate of 10Hz with accuracy of ± 2 m$ RMS horizontal, ± 5 m$ RMS vertical. * Current and Voltage: Mauch Electronics PL-200 sensor. This sensor can record currents up to 200 A and voltages up to 33 V. Analogue readings from the sensor were converted into a digital format using an 8 channel 17 bit analogue-to-digital converter (ADC). Data syncing and recording was handled using the Robot Operating System (ROS) running on a low-power Raspberry Pi 4. Data was recorded on the Raspberry Pi's microSD card. The data provided by each sensor were synchronized to a frequency of approximately 5Hz using the ApproximateTime message filter policy of Robot Operating System (ROS). The number of flights performed varying operational parameters (payload, altitude, speed) was 75.

本实验旨在通过实证手段测量电动垂直起降（Vertical Takeoff and Landing, VTOL）无人机（Unmanned Aerial Vehicles, UAVs）的能耗。我们自主操控MakeFlyEasy Fighter型VTOL无人机完成起飞、挂载不同重量载荷并沿两种飞行模式飞行、着陆的全流程。在各次飞行之间，我们通过一组离散选项调整指定运行参数：载荷分别为0g、400g与800g；巡航高度设为50m与100m；巡航速度设为18m/s与22m/s。
实验过程中，我们同时从多类机载传感器中采集数据。本次实验使用的机载传感器如下：
1. 风速传感器：采用FT Technologies FT205型可适配无人机的预校准超声风速传感器，测量精度为±0.1m/s，采样刷新率为10Hz；
2. 位置传感器：采用3DM-GX5-45型GNSS/惯性导航系统（INS）传感器套件。该传感器内置卡尔曼滤波系统，可融合GPS与惯性测量单元（Inertial Measurement Unit, IMU）数据，最大输出频率为10Hz，水平定位精度为±2m均方根（RMS），垂直定位精度为±5m均方根（RMS）；
3. 电流与电压传感器：采用Mauch Electronics PL-200型传感器。该传感器可记录最大200A的电流与最高33V的电压，其模拟读数通过8通道17位模数转换器（Analogue-to-digital converter, ADC）转换为数字格式。
数据同步与记录工作由运行于低功耗树莓派4（Raspberry Pi 4）上的机器人操作系统（Robot Operating System, ROS）完成，采集的数据存储于树莓派的microSD存储卡中。我们通过机器人操作系统（ROS）的ApproximateTime消息过滤策略，将各传感器采集的数据同步至约5Hz的采样频率。本次实验中，调整运行参数（载荷、高度、速度）的飞行次数总计75次。