Dataset of A Multi-Drone System Proof of Concept for Forestry Applications

The dataset presented in this study originates from a multi-drone proof of concept designed for efficient forest mapping and autonomous operation, conducted within the framework of the OPENSWARM EU Project. It comprises data collected from field experiments where multiple drones collaboratively navigated and mapped a forest environment. The dataset includes sensor data from state-of-the-art open-source SLAM frameworks, such as LiDAR-Inertial Odometry via Smoothing and Mapping (LIO-SAM) and Distributed Collaborative LiDAR SLAM (DCL-SLAM). These frameworks were integrated within the MRS UAV System and Swarm Formation packages, utilizing Robot Operating System (ROS) middleware. The recorded data consists of LiDAR point clouds, IMU readings, GPS trajectories, and system logs, capturing the drones' performance in complex, real-world forestry conditions. Additionally, flight control parameters optimized using an auto-tuning particle swarm optimization method are included to support reproducibility and further analysis. This dataset aims to facilitate research in autonomous multi-drone systems for forestry applications, offering valuable insights for scalable and sustainable forest management solutions.