{'fraction_non_alphanumeric': 0.015957446808510637, 'fraction_numerical': 0.003989361702127659, 'mean_word_length': 5.663716814159292, '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}}
Comparative Study of 3-Dimensional Path Planning Methods Constrained by the Maneuverability of Unmanned Aerial Vehicles

This paper presents a comparison of two classic path planning techniques, Rapidly-Exploring Random Tree and Modified Adaptive Cell Decomposition applied to 3-Dimensional space path planning generation for UAVs. The study presented focuses on the inclusion of real fixed-wing UAVs maneuverability, where the dynamic and kinematic behaviour introduces hard constraints in real environments. In addition, the inclusion of Dubins and Clotoids curves in 3-Dimensional spaces has been considered in terms of improving the results of these classical methods. Flight simulation results have been included to clarify this comparative study.