Coverage Path Planning for Spraying Drones

Vazquez-Carmona, E. Viridiana; Vasquez-Gomez, J. Irving; Lozada, Juan Carlos Herrera; Antonio-Cruz, Mayra

The pandemic by COVID-19 is causing a devastating effect on the health of global population. There are several efforts to prevent the spread of the virus. Among those efforts, cleaning and disinfecting public areas have become important tasks. In order to contribute in this direction, this paper proposes a coverage path planning algorithm for a spraying drone, a micro aerial vehicle that has mounted a sprayer/sprinkler system, to disinfect areas. In contrast with planners in the state-of-the-art, this proposal presents i) a new sprayer/sprinkler model that fits a more realistic coverage volume to the drop dispersion and ii) a planning algorithm that efficiently restricts the flight to the region of interest avoiding potential collisions in bounded scenes. The drone with the algorithm has been tested in several simulation scenes, showing that the algorithm is effective and covers more areas with respect to other approaches in the literature. Note that the proposal is not limited to disinfection applications, but can be applied to other ones, such as painting or precision agriculture.