Planejamento de trajetórias para quadricópteros utilizando o método RRT

Abstract

In an attempt to facilitate many activities that can be complex, dangerous and even impossible for humans, unmanned aerial vehicles (UAVs) have been gaining ground. UAVs can be remotely piloted or autonomous and are used in a variety of situations, such as leisure, military use, agriculture and industry, such as the inspection of equipment in classified areas, as these are areas with an explosive atmosphere and are not suitable for continuous human work. Autonomous UAVs encounter some difficulties, since without someone piloting and not knowing the environment, they need to be able to avoid obstacles, so there is a need to study trajectory planning. Theoretically, there are several methods that solve this problem, with different advantages and disadvantages, many were developed only for 2D environments, in others it is essential to have complete knowledge of the environment map. Furthermore, it is necessary to carry out practical tests to validate the methods, which is not yet a reality for everyone. The present work aims to understand these methods and delve deeper into the chosen method called Rapidly-Exploring Random Tree. To this end, simulations and real tests are carried out for different scenarios, considering a pre-determined environment and static obstacles to validate the method and, in the future, be able to use it in everyday situations.