OPTIMIZATION OF UAV PATH PLANNING ALGORITHMS FOR EFFECTIVE ACCESS AND BACKHAUL COVERAGE

Abstract

This research project is aimed on the optimization of Unmanned Aerial Vehicle (UAV) path planning algorithms and backhaul coverage. The study depicts numerous path planning algorithms, including A-Star, Dijkstra, and Rapidly-Exploring Random Tree (RRT). Also, the research analyzes productivity beneath diverse natural conditions. Via simulations in a software, the impact of assorted variables such as wind speed, direction and trajectory arranging on UAV performance is analyzed. The results highlight the advantages and disadvantages of each algorithm tested and propose crossover frameworks to improve coverage, energy efficiency, and adaptability in changing situations. The results recommend that optimized path planning algorithms can significantly progress UAV-based communication frameworks, making them a dependable arrangement for diverse applications in rural and urban regions.