Article
Version 2
This version is not peer-reviewed
Energy-Optimized 3D Path Planning for Unmanned Aerial Vehicle
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and
Version 1
: Received: 17 July 2024 / Approved: 18 July 2024 / Online: 18 July 2024 (11:28:28 CEST)
Version 2 : Received: 30 July 2024 / Approved: 30 July 2024 / Online: 30 July 2024 (11:54:57 CEST)
Version 2 : Received: 30 July 2024 / Approved: 30 July 2024 / Online: 30 July 2024 (11:54:57 CEST)
How to cite: Nagy, I.; Laufer, E. Energy-Optimized 3D Path Planning for Unmanned Aerial Vehicle. Preprints 2024, 2024071465. https://doi.org/10.20944/preprints202407.1465.v2 Nagy, I.; Laufer, E. Energy-Optimized 3D Path Planning for Unmanned Aerial Vehicle. Preprints 2024, 2024071465. https://doi.org/10.20944/preprints202407.1465.v2
Abstract
Drone technology has undoubtedly become an integral part of our everyday life these days. The business and industrial use of unmanned aerial vehicles (UAV) can provide advantageous solutions in many areas of life, and they are also optimal for emergency situations and for accessing hard-to-reach places. However, their application poses numerous technological and regulatory challenges to be overcome. One of the weak links in the operation of UAVs is the limited availability of energy. In order to address this issue authors developed a novel trajectory planning method for UAVs to optimize the energy necessity during flight. First, an “energy map” was created, which was the basis for trajectory planning, i.e., determining the energy consumption of the individual components. This was followed by configuring the 3D environment including partitioning of the work space (WS), in fact, defining the free spaces, occupied spaces (obstacles) and semi-occupied/free spaces. Then the corresponding graph-like path(s) were generated on the basis of the partitioned space, where a graph search-based heuristic trajectory planning was initiated, taking into account the most important wind conditions including velocity and direction. Finally, in order to test the theoretical results, some sample environments were created to test and analyse the proposed path generations. The method eventually proposed was able to determine the optimal path in terms of energy consumption.
Keywords
UAV; trajectory planning; trajectory optimization; 3D environment; energy map
Subject
Engineering, Aerospace Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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