An Analysis on the Energy Consumption of Coverage Path Planning Algorithms on Multiple UAVs

One of the greatest limitations that aerial vehicles face nowadays is the limitation in flight durations. This issue becomes more critical in search applications where a specific area is required to be covered through drone using Coverage Path Planning (CPP) algorithms. Searching in bigger regions multiple drones are often deployed to cover an area. This work utilized multiple combinations of UAVs using different CPP algorithms to find the most optimal choice to cover a region. There were four simulation scenarios with the above-mentioned combinations which were evaluated for multiple parameters. These parameters include coverage completeness, coverage time, battery consumption and the number of maneuvers required to cover the region using ROS Gazebo Simulation and Qground Control. The data retrieved from the simulation results were then compared to determine the best CPP method. It was observed from the results that the Expanding Spiral method proved to be the fastest CPP method with the least coverage time, lowest battery consumption and least number of turns.