Energy-aware Multi-UAV Coverage Mission Planning with Optimal Speed of Flight
<|reference_start|>Energy-aware Multi-UAV Coverage Mission Planning with Optimal Speed of Flight: This paper tackles the problem of planning minimum-energy coverage paths for multiple UAVs. The addressed Multi-UAV Coverage Path Planning (mCPP) is a crucial problem for many UAV applications such as inspection and aerial survey. However, the typical path-length objective of existing approaches does not directly minimize the energy consumption, nor allows for constraining energy of individual paths by the battery capacity. To this end, we propose a novel mCPP method that uses the optimal flight speed for minimizing energy consumption per traveled distance and a simple yet precise energy consumption estimation algorithm that is utilized during the mCPP planning phase. The method decomposes a given area with boustrophedon decomposition and represents the mCPP as an instance of Multiple Set Traveling Salesman Problem with a minimum energy objective and energy consumption constraint. The proposed method is shown to outperform state-of-the-art methods in terms of computational time and energy efficiency of produced paths. The experimental results show that the accuracy of the energy consumption estimation is on average 97% compared to real flight consumption. The feasibility of the proposed method was verified in a real-world coverage experiment with two UAVs.<|reference_end|>
@article{datsko2024energy-aware,
    title={Energy-aware Multi-UAV Coverage Mission Planning with Optimal Speed of
  Flight},
    author={Denys Datsko, Frantisek Nekovar, Robert Penicka, Martin Saska},
    journal={IEEE Robotics and Automation Letters, vol. 9, no. 3, pp.
  2893-2900, March 2024},
    year={2024},
    doi={10.1109/LRA.2024.3358581},
    archivePrefix={arXiv},
    eprint={2402.10529},
    primaryClass={cs.RO}
}