Data Collected with Package Delivery Quadcopter Drone
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
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 195. In addition, 14 recordings were done to assess the drone’s ancillary power and hover conditions.