Rocha, Lidia (UFSCar), Kelen, Vivaldini (UFSCar)

A 3D Benchmark for UAV Path Planning Algorithms: Missions Complexity, Evaluation and Performance

Scheduled for presentation during the Regular Session "Path Planning I" (WeB4), Wednesday, June 22, 2022, 16:30−16:50, Divona-2

2022 International Conference on Unmanned Aircraft Systems (ICUAS), June 21-24, 2022, Dubrovnik, Croatia

This information is tentative and subject to change. Compiled on April 23, 2024

Abstract

Unnamed Aerial Vehicles can carry out several missions. It is essential to use path planning algorithms to obtain an efficient trajectory without collision to complete these missions. Several path planning algorithms in the literature are divided into four categories: exact classic, approximate classic, meta heuristic, and machine learning. However, it is not easy to define which is the best for each mission among all path planning algorithms. In this context, an analysis between these categories can facilitate research determining the techniques that obtain better results in each UAV mission. So, in this work, we contribute a deep benchmarking of 3D path planning techniques in a simulated and real environment. As a result, classical techniques demonstrate better capacities in dynamic path planning. On the other hand, meta heuristic and machine learning techniques performed the best results for static path planning.