Collision cone based time-efficient method for 3D collision avoidance for UAVs: A purely heading-based solution

The increasing deployment of unmanned aerial vehicles (UAVs) across various fields, from agriculture to disaster management, has raised critical concerns about mid-air collisions in increasingly congested airspaces. While previous research has extensively explored collision avoidance techniques, most solutions focus either on static or low-density dynamic environments, leaving a gap in addressing UAV navigation in densely cluttered, dynamic 3D environments. This paper introduces a novel collision cone-based approach designed to enhance time-efficiency and precision in 3D UAV collision avoidance scenarios, particularly in complex and dynamic environments with multiple obstacles. Through both simulation and real-world experiments, the method demonstrates superior time-efficiency compared to a benchmark method, while maintaining robust performance in unpredictable environments. The contributions of this work include the development of a real-time adaptable algorithm that recalculates optimal paths based on dynamic changes and its practical validation in realistic, high-density scenarios. This work fills a significant research gap by addressing the limitations of previous 2D approaches and static obstacle methods, providing a comprehensive solution for UAVs operating in highly dynamic 3D spaces.