Data Collected with Package Delivery Quadcopter Drone

This experiment was performed in order to empirically measure the energy use of small, electric Unmanned Aerial Vehicles (UAVs). We autonomously direct a DJI ® Matrice 100 (M100) drone to take off, carry a range of payload weights on a triangular flight pattern, and land. Between flights, we varied specified parameters through a set of discrete options, payload of 0 , 250 g and 500 g; altitude during cruise of 25 m, 50 m, 75 m and 100 m; and speed during cruise of 4 m/s, 6 m/s, 8 m/s, 10 m/s and 12 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 Zero W. 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 196. In addition, 13 recordings were done to assess the drone’s ancillary power and hover conditions.

本实验旨在通过实证手段测量小型电动无人驾驶飞行器（Unmanned Aerial Vehicles, UAVs）的能耗。我们自主操控大疆（DJI）经纬Matrice 100（M100）无人机完成起飞、搭载指定有效载荷并沿三角航迹飞行后着陆。每次飞行间隙，我们通过一组离散参数组合调整实验设定，具体包括0 g、250 g与500 g的有效载荷，25 m、50 m、75 m及100 m的巡航高度，以及4 m/s、6 m/s、8 m/s、10 m/s与12 m/s的巡航速度。

我们同时从机载多传感器阵列中采集各类数据，所用传感器如下：
1. 风速传感器：FT Technologies FT205 适用于无人机的预校准超声风速传感器，测量精度为±0.1 m/s，刷新率为10 Hz；
2. 位置传感器：3DM-GX5-45 GNSS/INS 传感器组件。该传感器内置卡尔曼滤波系统，用于融合GPS与惯性测量单元（Inertial Measurement Unit, IMU）数据，最大输出速率为10 Hz，水平定位精度为±2 m 均方根误差（Root Mean Square, RMS），垂直定位精度为±5 m 均方根误差（Root Mean Square, RMS）；
3. 电流与电压传感器：Mauch Electronics PL-200 传感器。该传感器可测量最大200 A的电流与最大33 V的电压，其模拟量读数通过8通道17位模数转换器（Analog-to-Digital Converter, ADC）转换为数字格式。

数据同步与记录由运行于低功耗树莓派（Raspberry Pi）Zero W上的机器人操作系统（Robot Operating System, ROS）完成，数据存储于树莓派的microSD卡中。我们通过机器人操作系统（ROS）的近似时间消息过滤策略，将各传感器采集的数据同步至约5 Hz的采样频率。

本次实验中，针对有效载荷、巡航高度与巡航速度等运行参数的不同组合，共完成196次飞行。此外，我们还开展了13次飞行记录，用于评估无人机的辅助功耗与悬停工况。