Energy-Optimized 3D Path Planning for Unmanned Aerial Vehicles

Abstract

Drone technology has undoubtedly become an integral part of our everyday life in recent years. The business and industrial use of unmanned aerial vehicles (UAVs) 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, the authors developed a novel trajectory planning method for UAVs to optimize energy consumption 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), i.e., 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 analyze the proposed path generations. The method eventually proposed was able to determine the optimal path in terms of energy consumption.