TY - JOUR
T1 - Coverage path planning for spraying drones
AU - Vazquez-Carmona, E. Viridiana
AU - Vasquez-Gomez, Juan Irving
AU - Herrera-Lozada, Juan Carlos
AU - Antonio-Cruz, Mayra
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/6
Y1 - 2022/6
N2 - The pandemic by COVID-19 is causing a devastating effect on the health of the global population. Currently, there are several efforts to prevent the spread of the virus. Among those efforts, cleaning and disinfecting public areas have become important tasks and they should be automated in future smart cities. To contribute in this direction, this paper proposes a coverage path planning method for a spraying drone, an unmanned aerial vehicle that has mounted a sprayer/sprinkler system, that can disinfect areas. State-of-the-art planners consider a camera instead of a sprinkler, in consequence, the expected coverage will differ in running time because the liquid dispersion is different from a camera's projection model. In addition, current planners assume that the vehicles can fly outside the target region; this assumption can not be satisfied in our problem, because disinfections are performed at low altitudes. Our method presents i) a new sprayer/sprinkler model that fits a more realistic coverage volume to the drop dispersion and ii) a planning method that efficiently restricts the flight to the region of interest avoiding potential collisions in bounded scenes. The algorithm has been tested in several simulation scenes, showing that it is effective and covers more areas with respect to two 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.
AB - The pandemic by COVID-19 is causing a devastating effect on the health of the global population. Currently, there are several efforts to prevent the spread of the virus. Among those efforts, cleaning and disinfecting public areas have become important tasks and they should be automated in future smart cities. To contribute in this direction, this paper proposes a coverage path planning method for a spraying drone, an unmanned aerial vehicle that has mounted a sprayer/sprinkler system, that can disinfect areas. State-of-the-art planners consider a camera instead of a sprinkler, in consequence, the expected coverage will differ in running time because the liquid dispersion is different from a camera's projection model. In addition, current planners assume that the vehicles can fly outside the target region; this assumption can not be satisfied in our problem, because disinfections are performed at low altitudes. Our method presents i) a new sprayer/sprinkler model that fits a more realistic coverage volume to the drop dispersion and ii) a planning method that efficiently restricts the flight to the region of interest avoiding potential collisions in bounded scenes. The algorithm has been tested in several simulation scenes, showing that it is effective and covers more areas with respect to two 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.
KW - COVID-19
KW - Coverage
KW - Drone
KW - Path planning
KW - Smart cities
KW - Spraying
UR - http://www.scopus.com/inward/record.url?scp=85127497906&partnerID=8YFLogxK
U2 - 10.1016/j.cie.2022.108125
DO - 10.1016/j.cie.2022.108125
M3 - Artículo
C2 - 35370350
AN - SCOPUS:85127497906
SN - 0360-8352
VL - 168
JO - Computers and Industrial Engineering
JF - Computers and Industrial Engineering
M1 - 108125
ER -