# Swarm of Drones in a Simulation Environment--Efficiency and Adaptation
## 4 Simulation Experiments
### Scenario II
Drone swarms can be utilized in a variety of applications, from monitoring to rescue operations. These experiments can open new possibilities for their application in various fields. Simulation reduces the costs of testing real drones in various conditions. It allows a detailed verification of the swarm control concept using a leader-based mechanism and opens up new possibilities for the effective and safer use of drones. One such application could be swarms dedicated to drone shows. Currently, existing solutions rely on individually setting routes for all drones. The solution proposed in this article significantly facilitates the process of drone show preparation. Employing advanced simulation tools is a cost-effective method for testing and refining drone swarm operations and closely mirrors current environmental challenges and operational demands. In the case of this article, the simulation helped to develop a collision avoidance that preserves the distances between surrounding objects and swarm nodes. In our future works, we want to develop such systems. The most important task of the swarm coordination system is to maintain the geometric formation of drones. This task requires cyclical transmission of telemetry messages. This exchange is an example of standard point-to-point communication. As research has shown, this is one of the most important elements of a drone swarm management system. The conducted research demonstrated the influence of communication delays, drone swarm speed, and the accuracy of the positioning system on maintaining swarm structure and the safety of swarm movement. In the case of a positioning system based on RTK GPS (positioning accuracy 5 cm), with the distance between drones being 5 m, a swarm structure with a leader at one corner of the formation (Figure 4), and a maximum communication delay of 100 ms, safe flight was possible when the maximum speed of drones did not exceed 5 m/s. In case of the worse communications delay (500 ms), the maximum swarm speed was 4 m/s. In the case of another swarm structure (each subsequent drone follows its predecessor, Figure 5), the corresponding speeds were 2 m/s and 1 m/s. For a standard drone positioning system (accuracy 100 cm), safe flight was possible for the swarm structure with a single leader at the corner (Figure 4) and a maximum speed of 2 m/s. The results of these studies can be utilized in developing collision avoidance systems based on drone sensors (e.g., LIDAR, fisheye cameras, ultrasonic sensors, and others). In this scenario, the maximum communication delay can be treated as the maximum data processing time for sensors. The simulation research presented in the paper allows identifying the boundary conditions for efficient and effective drone swarm management. The determined boundaries will help us to determine appropriate drone hardware in future works. Additionally, we need to state that controlling a swarm of drones with a single leader is easier and results in fewer errors in maintaining the structure. The structure of a swarm in which each drone only looks at the drone in front of it requires a much better communication system, with significantly lower transmission delays. **Author Contributions:** Conceptualization, D.M., M.P., J.S. and K.W. ; methodology, D.M., M.P. and J.S. ; software, D.M., M.P., P.B. and J.S. ; validation, D.M., J.S. and M.S. ; formal analysis, D.M., J.S., M.S. and A.D.; investigation, M.P. and A.D.; resources, M.P. and M.K. ; data curation, J.S., P.B. and M.S. ; writing--original draft preparation, D.M., M.P., J.S. and A.D.; writing--review and editing, D.M., M.P., J.S. and A.D.; visualization, P.B., M.S. and M.K. ; supervision, M.P. and K.W. ; project administration, M.P. and K.W. ; funding acquisition, K.W. All authors have read and agreed to the published version of the manuscript.