Hazardous Area Aware Path-Planning for Drone Swarms
Vinh Quach, Burak Tüfekçi, Cihan Tunc, Ram Dantu · 2024
Path-planning for drones in areas with complex and unknown environments, constrained by various obstacles, presents a significant challenge in drone operations. This problem extends beyond merely finding an appropriate path from the starting point to the destination; it also involves selecting the ideal path among all available options based on given conditions. In this paper, we propose a novel smart path planning algorithm based on the Breadth-First Search (BFS) algorithm, taking into account both swarm energy and task completion. Performance metrics include the percentage of tasks completed, unachievable, and incomplete. Our novel algorithm demonstrates a significant improvement over traditional methods, outperforming them by an average of 10-15% in task completion. In extreme cases, this margin increases to nearly 20%. Analysis of unachievable tasks reveals that our method greatly reduces their occurrence. This research underscores the potential of our novel algorithm in enhancing operational performance for drone-based tasks, especially in hazardous contexts.