In-flight positional and energy use data set of a DJI Matrice 100 quadcopter for small package delivery

TL;DR

This paper presents a comprehensive dataset from 209 autonomous drone flights, capturing detailed sensor data across various operational parameters to aid research in UAV design, safety, and energy efficiency.

Contribution

The authors collected and validated a large, high-resolution dataset from 209 drone flights with varied parameters, providing valuable data for UAV research and development.

Findings

Collected 209 flights totaling 10 hours 45 minutes

Data includes GPS, IMU, voltage, current, and wind measurements

Validated data consistency across similar operational parameters

Abstract

We autonomously direct a small quadcopter package delivery Uncrewed Aerial Vehicle (UAV) or "drone" to take off, fly a specified route, and land for a total of 209 flights while varying a set of operational parameters. The vehicle was equipped with onboard sensors, including GPS, IMU, voltage and current sensors, and an ultrasonic anemometer, to collect high-resolution data on the inertial states, wind speed, and power consumption. Operational parameters, such as commanded ground speed, payload, and cruise altitude, are varied for each flight. This large data set has a total flight time of 10 hours and 45 minutes and was collected from April to October of 2019 covering a total distance of approximately 65 kilometers. The data collected were validated by comparing flights with similar operational parameters. We believe these data will be of great interest to the research and industrial communities, who can use the data to improve UAV designs, safety, and energy efficiency, as well as advance the physical understanding of in-flight operations for package delivery drones.