A Methodology for Measuring Flight Speed of Drones in Indoor Environments

Abstract Drones have become widespread in a wide range of fields. To calculate the energy model of drone, it is important to measure the flight speed automatically and accurately. However, acceleration-sensor-based or GPS-based flight speed measurement doesn’t give an accurate result. To solve this problem, an image-processing-based flight speed measurement method is proposed in this paper. Four cameras are employed to capture the images of the drone and an algorithm is proposed to synchronize these four cameras to get a higher accuracy. Experiments are conducted indoors so that it can be measured without the effect of wind. We compare the results of the purposed algorithm and human observations. Experimental results show that the proposed algorithm measures the flight speed correctly.

[1]  Gil Nachmani,et al.  Minimum-energy flight paths for UAVs using mesoscale wind forecasts and approximate dynamic programming , 2007 .

[2]  Beeshanga Abewardana Jayawickrama,et al.  Comprehensive Energy Consumption Model for Unmanned Aerial Vehicles, Based on Empirical Studies of Battery Performance , 2018, IEEE Access.

[3]  Sebastian Magierowski,et al.  Vehicle Routing Problems for Drone Delivery , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[4]  Ryan N. Smith,et al.  Wind-energy based path planning for Unmanned Aerial Vehicles using Markov Decision Processes , 2013, 2013 IEEE International Conference on Robotics and Automation.

[5]  Armin Zimmermann,et al.  An empirical study on generic multicopter energy consumption profiles , 2017, 2017 Annual IEEE International Systems Conference (SysCon).

[6]  Ittetsu Taniguchi,et al.  Power Measurement and Modeling of Quadcopters on Horizontal Flight , 2017, 2017 Fifth International Symposium on Computing and Networking (CANDAR).

[7]  Khaled M. Elbassioni,et al.  Autonomous Recharging and Flight Mission Planning for Battery-Operated Autonomous Drones , 2017, IEEE Transactions on Automation Science and Engineering.

[8]  Ittetsu Taniguchi,et al.  Work-in-Progress: Routing of Delivery Drones with Load-Dependent Flight Speed , 2019, 2019 IEEE Real-Time Systems Symposium (RTSS).

[9]  Nicholas R. J. Lawrance,et al.  Wind Energy Based Path Planning for a Small Gliding Unmanned Aerial Vehicle , 2009 .

[10]  Mohammad Marufuzzaman,et al.  Drones for disaster response and relief operations: A continuous approximation model , 2017 .