Advanced Obstacle Detection and Collision Avoidance in Swarm UAV Systems

Tata Sudiyanto, Vishnu Kumar Kaliappan

Abstract


This paper addresses the critical need for advanced obstacle detection and collision avoidance mechanisms in swarm Unmanned Aerial Vehicle (UAV) systems. We propose a framework that integrates computer vision, machine learning, and sensor fusion techniques to enhance the situational awareness of swarm UAVs. The study focuses on developing real-time algorithms capable of identifying obstacles and predicting potential collisions in dynamic environments. Experimental results validate the effectiveness of the proposed methods, demonstrating improved safety and operational efficiency in swarm missions. This research contributes to the ongoing development of intelligent swarm UAV systems capable of autonomous operation in complex and unpredictable environments.

Keywords


obstacle detection, collision avoidance, swarm UAV, situational awareness

References


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