Otonom İnsansız Hava Araçları için Dinamik ve Sabit Engellerle Çarpışmayı Önleme

Öz

İHA otonom navigasyonunun ilerlemesi, özellikle gerçek zamanlı çarpışma önleme alanında, hızlı ve istikrarlı olarak ilerlemektedir. Bu çalışmada, voksel tabanlı çevresel model oluşturmak için LiDAR veri analizini ve hareketli nesne yörüngelerini tahmin etmek için optik akışı (OF) kullanan bir çözüm önerildi. Önerilen sistem ,LiDAR'ın yüksek çözünürlüklü mekansal verilerini OF'nin göreceli hareket algılama yeteneğiyle birleştirerek, hareket halindeyken hem statik hem de dinamik nesnelerin algılanmasını ve bunlardan kaçınılmasını sağlar. Bu sayede bütünsel bir algılama sistemi esas alınarak İHA'nın ortamdaki her türlü değişime uyum sağlayabilmesi ve seyir otonomisinin artırılması sağlanabilecektir.Çok katmanlı bileşenler sayesinde, önerilen çarpışma önleme algoritması, çok sayıda farklı koşulda İHA operasyonları için etkili bir şekilde güvenlik sağlayabilmektedir. Deney ve simülasyon sonuçları, sistemin az-ışıklı veya yüksek hızlı bileşenlerin dahil olduğu durumlarda İHA'nın uçuş yolunu sabit tutabildiğini göstermektedir.

Anahtar Kelimeler

• LiDAR
• Optical flow
• UAV
• Sensor Fusion
• Trajectory Planning
• Collision Avoidance

Collision Avoidance for Autonomous Unmanned Aerial Vehicles with Dynamic and Stationary Obstacles

Öz

The progress of UAV autonomous navigation is steadily progressing at a much faster pace, especially in the field of real-time collision avoidance. In this study, an all-in-one solution proposed that uses a LiDAR data analysis for voxel-based environmental model creation and an optical flow (OF) for predicting moving object trajectories. By fusing LiDAR’s high-resolution spatial data with the relative motion detection capability of the OF, proposed system enables detection and avoidance of both static and dynamic objects on-the-fly. In this regard, based on a holistic perception system, the UAV can adapt to any changes in the environment, and its navigational autonomy can be enhanced. Due to these multi-tiered components, this collision avoidance algorithm is able to efficiently provide safety for UAV operations in a vast number of various conditions. Experiment and simulation results indicate that the system is capable to keep the UAV’s flight path steady through various situations where low-light or high-speed components are involved.

Anahtar Kelimeler

• LiDAR
• Optical flow
• UAV
• Sensor Fusion
• Trajectory Planning
• Collision Avoidance

Kaynakça

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