Flight planning in multi-unmanned aerial vehicle systems: Nonconvex polygon area decomposition and trajectory assignment

Abstract

Nowadays, it is quite common to have one unmanned aerial vehicle (UAV) working on a task but having a team of UAVs is still rare. One of the problems that prevent us from using teams of UAVs more frequently is flight planning. In this work, we present the first open-source solution ( https://pypi.org/project/pode/ ) for splitting any complex area into multiple parts. The area of interest can be convex or nonconvex and can include any number of no-flight zones. Four solutions, based on the algorithm of Hert and Lumelsky, are tested with the aim of improving the compactness of the partitions. We also show how the shape of the partitions influences flight performance in a real case scenario.

Multi-Robot Workspace Division Based on Compact Polygon Decomposition

“…This algorithm is based on the most compact partition of a polygon into two parts. The performance and the quality of the obtained results were compared against an algorithm described in [20] and [33], and against an approach with brute-force search over a discretized polygon border. It was shown that the algorithm presented in this paper is more efficient and the resulting parts show much better quality in terms of compactness.…”

“…In this section, we show the quality of the results obtained with our algorithm compared against two different approaches. The first approach is the algorithm from [20] implemented in [33]. The second approach is a naive approach.…”

“…Next, we also check the performance of our implementation of the algorithm of [20] implemented in [33]. Fig.…”

“…The algorithm was tested only on a single rectangle, so more tests are needed to understand if it works for more complex cases. In our previous work [33] the same algorithm for dividing non-convex polygons was implemented with several extensions. It was shown that performing the initial partition into convex parts has a big effect on the quality of the resulting partition.…”

“…The core idea of the algorithm is that it is possible to calculate analytically the best possible way to divide a polygon into two parts for a given area requirement in terms of the perimeter of the corresponding part. We will present a theory behind the algorithm, and compare the results with two different approaches, one of which is taken from the aforementioned paper [33] and the other one is based on discretizing the polygon border into a set of vertices and brute-force search for the most compact solution.…”