# Designing UAV Swarm Experiments: A Simulator Selection and Experiment Design Process
## 2 Background and Motivation
Based on our analysis, we have summarized our findings in the following figures and tables. Figure 1 shows the top six platforms that were used by researchers working on aerial robotic swarms in the past five years. Table 2 presents additional information about simulation platforms examined such as OS support and cross-platform availability. Table 3 lists notable publications on swarm robotic development in the past three years (2021-2023) along with the simulation platform used for experiments and result validation. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Name** & **OS Support 1** & **UAV Specific?** & **Possibility of Cross-Platform Connectivity 2** & **Notable Publication by Platform Creators** & **Remarks** \\ \hline Gazebo & W*, M*, L & No & Yes & — & — \\ Webots & W, M, L & No & Yes & — & Independent simulation platform with support for various robot platforms. \\ CoppeliaSim & W, M, L & No & Yes & [23] & Formerly known as VREP. Although MATLAB is not UAV specific, the UAV toolbox is designed for UAV development. & \\ RflySim & W & No & Yes & [28] & Independent simulation platform inspired by PX4 and MATLAB simulation platform. \\ ARG6S & M*, L & No & Yes* & [29] & Multiphysics robot simulator. \\ OMNET++ & W, M, L & No & Yes & — & Discrete event simulation platform focused on networking and communication. \\ AVENS & W & Yes & Yes & [30] & Works with the OMNET++ network simulator and X-Plane flight simulator. \\ MORSE & W*, M*, L* & No & Yes & [31] & — \\ \hline \hline \end{tabular}  
* \({}^{1}\) A
* near the OS label indicates that direct binaries of the tool may not be available; however, alternatives such as docker deployments or community supported guides do exist. 2 A + near the yes indicates that the software has indirect passing of model data for cross-platform connectivity or the possibility of self-developed plug-ins.  
\end{table} 
Table 2: Simulation tools examined. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference** & **Year Published** & **Study Description** & **Platform Used 1** \\ \hline
[32] & 2021 & Formation control of heterogeneous UAV and USV swarms. & CoppeliaSim \\ \hline
[33] & 2021 & Architecture of UAV swarm to find a load and transport it to its destination cooperatively. & CoppeliaSim \\ \hline
[34] & 2021 & Adaptive formation control for UAV swarms with multiple leaders and switching topologies. & Gazebo \\ \hline
[35] & 2021 & Control of UAV agents in a swarm using vision-based approaches. & Gazebo \\ \hline
[36] & 2021 & Development of control layers to enable the autonomous and cooperative navigation of a swarm of UAVs. & Gazebo \\ \hline
[37] & 2021 & Optimized area coverage by autonomous multi-UAV. & Gazebo + MATLAB problems in multi-UAV. & Gazebo \\ \hline
[38] & 2021 & Approach to address coverage and flocking problems in multi-UAV. & Gazebo \\ \hline
[39] & 2021 & Bioinspired neural network for cooperative planning of multi-UAV. & Gazebo \\ \hline
[40] & 2021 & Safe allocation of UAV swarm mission resources based on random labels. & OMNET++ \\ \hline
[41] & 2022 & Coverage and path planning algorithm for swarms to detect points of interest and collect information from them. & OMNET++ \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Recent work on UAV swarm development and the simulation platform they used is categorized by published year (Range 2021 to 2023).