Path Planning of Multi Drone System for Disaster Analysis and Management

Disasters often cause unpredictable damage that complicates emergency response efforts. While drones (UAVs) offer promise for accessing hard-to-reach areas, current systems lack robust autonomous navigation and 3D situational awareness needed for efficient disaster management. This paper presents a novel approach using multiple drones to collaboratively generate detailed 3D models and employs an advanced deep learning-based obstacle detection and 3D path-planning system. Extending traditional 2D algorithms into 3D, our method integrates new cost functions to optimise drone swarm navigation considering environmental and operational constraints. Using pre-disaster 3D maps and real-time data, the system enables faster, safer, and more efficient search and rescue operations. Validated in AirSim simulations, this framework significantly enhances UAV autonomy and coordination, addressing key limitations in current disaster response technologies and improving both pre- and post-disaster management strategies.