Autonomous UAV Flight in Urban Environments: Challenges and Solutions

Abstract

Autonomous flight in urban environments presents unique challenges for Unmanned Aerial Vehicles (UAVs) due to complex structures, dynamic obstacles, and regulatory constraints. This paper identifies key challenges associated with urban UAV operations and proposes solutions that leverage advanced perception, navigation, and control techniques. We explore the integration of computer vision, sensor fusion, and machine learning algorithms to enhance situational awareness and obstacle avoidance capabilities. Experimental results illustrate the effectiveness of the proposed solutions in navigating urban landscapes while ensuring safety and compliance with regulations. This research contributes to the development of robust autonomous UAV systems capable of operating in complex urban environments.