Rerouting UAVs in Dynamic Environment Based on Optimised Interfered Fluid Dynamical System

Abstract Navigating unmanned aerial vehicles (UAVs) through areas full of obstacles is a complex task. Traditional path planning methods, which rely on pre-generated paths, fall short in real-world scenarios where dynamic obstacles are introduced. To ensure mission success, UAVs must reroute dynamically to avoid collisions. The need for real-time decision-making further complicates this dynamic path-planning problem. We have developed a novel dynamic path-planning algorithm to address these challenges based on the Interfered Fluid Dynamical System (IFDS) framework. Drawing inspiration from how water naturally flows around obstacles, the IFDS algorithm adapts to changing environments to generate paths. We have augmented IFDS with environmental data, such as weather and terrain, to enhance its path calculations and optimise it using numerical methods. Every aspect of the algorithm is expressed in a closed form, enabling efficient real-time execution even in a three-dimensional environment, making our solution particularly suited for real-world UAV navigation.