Motion Planning for Aggressive Flights of an Unmanned Aerial Vehicle

Abstract: Unmanned aerial vehicles are becoming more popular in today’s society, which results in the rise of laws intended to maintain safety. To abide by these, while allowing the technology to expand, functioning path-planning algorithms are required.This also includes having methods for detecting and managing obstacles. This project aims to improve an existing path-planning algorithm that is based on A' and implemented in Python.The solution consisted of using functions for finding polytopeintersection,as well as optimizing the collision avoidance and the search algorithm. In addition to that, realistic constraints were implemented on the generated trajectory in order to reflect real-life limitations. The results demonstrated that the paths were always feasible, with respect to input and position constraints. The program’s computation time was also reduced up to 89% of the original run-time. There is, however, still room for improvement since the original code generated a shorter path for the three scenarios it was created for. On the other hand,the improved algorithm could handle a new scenario, which the original code failed to do.