STAR: Swarm Technology for Aerial Robotics Research

TL;DR

STAR is a cost-effective framework using low-cost drones and landmark-based localization to facilitate aerial swarm research, enabling more accessible experimentation and bridging the gap between theory and practice.

Contribution

The paper introduces a novel, affordable swarm robotics framework based on Crazyflie drones with enhanced localization and obstacle avoidance capabilities.

Findings

Successful implementation of a low-cost swarm platform

Enhanced localization accuracy with fiducial markers

Effective collision avoidance in experimental setups

Abstract

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.