  In recent years, the field of aerial robotics has witnessed significant
progress, finding applications in diverse domains, including post-disaster
search and rescue operations. Despite these strides, the prohibitive
acquisition costs associated with deploying physical multi-UAV systems have
posed challenges, impeding their widespread utilization in research endeavors.
To overcome these challenges, we present STAR (Swarm Technology for Aerial
Robotics Research), a framework developed explicitly to improve the
accessibility of aerial swarm research experiments. Our framework introduces a
swarm architecture based on the Crazyflie, a low-cost, open-source, palm-sized
aerial platform, well suited for experimental swarm algorithms. To augment
cost-effectiveness and mitigate the limitations of employing low-cost robots in
experiments, we propose a landmark-based localization module leveraging
fiducial markers. This module, also serving as a target detection module,
enhances the adaptability and versatility of the framework. Additionally,
collision and obstacle avoidance are implemented through velocity obstacles.
The presented work strives to bridge the gap between theoretical advances and
tangible implementations, thus fostering progress in the field.
