This paper addresses the problem of maximizing surveillance area coverage using multiple Unmanned Aerial Vehicles (UAVs) in an obstacle-laden and Global Positioning System (GPS)-denied environment. The UAVs should achieve this objective using the shortest possible routes while staying inside the designated search space and avoiding the obstacles. To attain a desired area coverage, we divide the NP-hard multi-objective optimization problem of planning optimal routes for all UAVs into 3 parts: (a) optimizing search area coverage, (b) performing obstacle avoidance, and (c) using Cooperative Localization (CL) for state estimation. We demonstrate the efficiency of our algorithm through extensive simulations.
Cooperative Search Area optimization using Multiple Unmanned Aerial Vehicles in a GPS-denied Environment
01.06.2019
641250 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch