Evaluating the effectiveness of takeoff assignment strategies under irregular configurations

The use of UAVs has been growing steadily over the last years. Now that even the industry is adopting them for a wide range of activities, it can be said with certainty that UAVs will become an important asset for many enterprises. We foresee that, due to affordable prices, applications with groups of UAVs, also called swarms, will become mainstream. Swarms of UAVs can perform tasks faster and/or with more redundancy, and other tasks are only possible by collaborative work of UAVs. However, there are still many challenges to be solved before swarms of UAVs can be used safely. One of the challenges is the takeoff; i.e., takeoff should be safe (no collisions) and fast at the same time. An important part of the takeoff is the assignment task; i.e., determining which UAV goes where. In this work we will compare the effectiveness of three assignment algorithms, in terms of total distance travelled, number of flight paths crossing, and calculation time. We specially focus on irregular patterns. Our results show that the Kuhn-Munkres Algorithm (KMA) is preferable in almost all cases. It ensures that the total distance travelled by all UAVs is minimal, and most importantly it reduces the number of flight paths crossing each other (i.e. potential collisions). This is a very important metric because it allows for fast (semi) simultaneous takeoff procedures, which are not possible if the chances of collision are high.