非GNSS環境におけるLiDAR SLAMを用いた飛行ドローンの自律障害物回避

抄録

This study addresses the challenge of autonomous drone flight in environments where GNSS is unavailable, using only onboard sensors like LiDAR and IMU. Focusing on obstacle avoidance without external sensors, we employ LiDAR-based SLAM for real-time 3D mapping and localization, enabling stable flight in diverse settings such as indoor spaces and densely built areas. Our method innovates by mapping environments on-the-fly and applying an extended artificial potential method for navigation, avoiding the common pitfalls of local minima. Simulation results demonstrate the drone's ability to autonomously reach target locations, underlining the potential of LiDAR SLAM for enhancing drone autonomy in GNSS-denied areas. This research lays the groundwork for future advancements in drone technology, promising wider application and efficiency in logistical operations and beyond.