Data Collect 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。我们操控一架MakeFlyEasy Fighter型垂直起降无人机自主完成起飞流程，在两种不同飞行模式下搭载多组不同重量的载荷，随后完成着陆。在两次飞行之间，我们通过一组离散配置调整指定运行参数：载荷分别设置为0g、400g与800g；巡航高度设置为50m与100m；巡航速度设置为18m/s与22m/s。

与此同时，我们从多台机载传感器中同步采集数据。本次实验使用的机载传感器包括：
1. 风速传感器：FT Technologies公司生产的FT205型可搭载式预校准超声风速传感器，测量精度为±0.1m/s，刷新频率为10Hz；
2. 位置传感器：采用3DM-GX5-45型全球导航卫星系统（Global Navigation Satellite System, GNSS）/惯性导航系统（Inertial Navigation System, INS）组合传感器组。该传感器内置卡尔曼滤波（Kalman filtering）系统，可融合全球定位系统（Global Positioning System, GPS）与惯性测量单元（Inertial Measurement Unit, IMU）的数据，最大输出频率为10Hz，水平测量精度为±2m均方根（Root Mean Square, RMS），垂直测量精度为±5m均方根（Root Mean Square, RMS）；
3. 电流与电压传感器：采用Mauch Electronics公司生产的PL-200型传感器。该传感器可测量最大200A的电流与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。

数据的同步与记录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）的近似时间（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。本次实验中共开展了75次改变运行参数（载荷、高度、速度）的飞行任务。

搜集汇总

背景与挑战

背景概述

该数据集包含电动垂直起降（VTOL）无人机在不同有效载荷、高度和速度参数下的75次飞行测试数据，用于测量能源使用情况。数据通过多种传感器收集，并使用ROS系统进行同步记录，适用于无人机能源模型研究。