EAOA: Energy-Aware Grid-Based 3D-Obstacle Avoidance in Coverage Path Planning for UAVs

Alia Ghaddar and Ahmad Merei
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Alia Ghaddar: Department of Computer Science, International University of Beirut, Beirut P.O. Box 146404, Lebanon
Ahmad Merei: Department of Computer Science, International University of Beirut, Beirut P.O. Box 146404, Lebanon

Future Internet, 2020, vol. 12, issue 2, 1-20

Abstract: The presence of obstacles like a tree, buildings, or birds along the path of a drone has the ability to endanger and harm the UAV’s flight mission. Avoiding obstacles is one of the critical challenging keys to successfully achieve a UAV’s mission. The path planning needs to be adapted to make intelligent and accurate avoidance online and in time. In this paper, we propose an energy-aware grid based solution for obstacle avoidance (EAOA). Our work is based on two phases: in the first one, a trajectory path is generated offline using the area top-view. The second phase depends on the path obtained in the first phase. A camera captures a frontal view of the scene that contains the obstacle, then the algorithm determines the new position where the drone has to move to, in order to bypass the obstacle. In this paper, the obstacles are static. The results show a gain in energy and completion time using 3D scene information compared to 2D scene information.

Keywords: coverage path planning; obstacle avoidance; unmanned aerial vehicle; energy consumption; completion time (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2020
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