{'fraction_non_alphanumeric': 0.030562347188264057, 'fraction_numerical': 0.0012224938875305623, 'mean_word_length': 5.768595041322314, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Cooperative Search Area optimization using Multiple Unmanned Aerial Vehicles in a GPS-denied Environment

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.