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

Thiago A. Rodrigues, Jay Patrikar , Arnav Choudhry , Jacob Feldgoise , Vaibhav Arcot , Aradhana Gahlaut , Sophia Lau , Brady Moon , Bastian Wagner , H. Scott Matthews , Sebastian Scherer , and Constantine Samaras
Published In the proceedings of Nature Scientific Data [SUBMITTED], 2021

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 dataset 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.

Figure shows the GPS route and sample data outputs from the onboard sensor array