Advancements in Object Detection for Unmanned Aerial Vehicles: Applications, Challenges, and Future Perspectives

Unmanned Aerial Vehicles (UAVs) are used in different fields ranging from recreational vehicles to agriculture, environmental monitoring, infrastructure inspection, disaster management, security, surveillance and logistics. This paper provides an overview of UAV applications and highlights the importance of object detection in improving drone autonomy. Object detection facilitates tasks such as precision agriculture, disaster response, environmental protection, infrastructure inspection and autonomous navigation. The paper reviews recent advances in UAV-specific object detection algorithms and methodologies and highlights challenges such as varying altitudes, motion blur, real-time processing constraints and limited computational resources. Solutions and adaptations are discussed to overcome these challenges, including lightweight neural network architectures, transfer learning, data augmentation, edge computing, multi-sensor fusion, attention mechanisms and adaptive algorithms. The study highlights the importance of integrating object detection systems into UAVs to improve their use in various sectors and contribute to improvements in surveillance missions.