TY - JOUR
T1 - Coverage Path Planning for 2D Convex Regions
AU - Vasquez-Gomez, Juan Irving
AU - Marciano-Melchor, Magdalena
AU - Valentin, Luis
AU - Herrera-Lozada, Juan Carlos
N1 - Publisher Copyright:
© 2019, Springer Nature B.V.
PY - 2020/1/1
Y1 - 2020/1/1
N2 - The number of two-dimensional surveying missions with unmanned aerial vehicles has dramatically increased in the last years. To fully automatize the surveying missions it is essential to solve the coverage path planning problem defined as the task of computing a path for a robot so that all the points of a region of interest will be observed. State-of-the-art planners define as the optimal path the one with the minimum number of flight lines. However, the connection path, composed by the path from the starting point to the region of interest plus the path from it to the ending point, is underestimated. We propose an efficient planner for computing the optimal edge-vertex back-and-forth path. Unlike previous approaches, we take into account the starting and ending points. In this article, we demonstrate the vertex-edge path optimality along with in-field experiments using a multirotor vehicle validating the applicability of the planner.
AB - The number of two-dimensional surveying missions with unmanned aerial vehicles has dramatically increased in the last years. To fully automatize the surveying missions it is essential to solve the coverage path planning problem defined as the task of computing a path for a robot so that all the points of a region of interest will be observed. State-of-the-art planners define as the optimal path the one with the minimum number of flight lines. However, the connection path, composed by the path from the starting point to the region of interest plus the path from it to the ending point, is underestimated. We propose an efficient planner for computing the optimal edge-vertex back-and-forth path. Unlike previous approaches, we take into account the starting and ending points. In this article, we demonstrate the vertex-edge path optimality along with in-field experiments using a multirotor vehicle validating the applicability of the planner.
KW - Computational geometry
KW - Coverage path planning
KW - Drone survey
KW - Optimal path
KW - Unmanned aerial vehicle
UR - http://www.scopus.com/inward/record.url?scp=85065731431&partnerID=8YFLogxK
U2 - 10.1007/s10846-019-01024-y
DO - 10.1007/s10846-019-01024-y
M3 - Artículo
AN - SCOPUS:85065731431
SN - 0921-0296
VL - 97
SP - 81
EP - 94
JO - Journal of Intelligent and Robotic Systems: Theory and Applications
JF - Journal of Intelligent and Robotic Systems: Theory and Applications
IS - 1
ER -