Multi-State Modelling for Real-time Localization & Mapping by UAVs

Abstract

Natural disasters such as flood, tsunami, earthquake and cyclones usually influence the microspores and in urban areas, thereby causing the problem to rescuers to make use of the UAV Localized Feature points. Rescue operations in these situations are also hampered due to darkness caused by power cut and unavailability of other light sources to rescue people in peril or to even carry out evacuation operations. Therefore, we need solution to map all the essential large-scale feature spaces to avail safety and saving numerous lives in disaster environments using Network Coded Feature set for Auto Neural Architecture Generator Algorithm (NCCA) to control positions & rotation of UAVs. Herein, we proposea multi-state modelling framework for Unmanned Aerial Vehicles (UAVs) for crisis mapping to control drones in real-time and at the same time allow map generation from aerial view essential feature points can be located to enable strategic planning operations.