{'fraction_non_alphanumeric': 0.011270491803278689, 'fraction_numerical': 0.0, 'mean_word_length': 5.262820512820513, '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}}
Obstacle avoidance for multi-UAV path planning based on particle swarm optimization

Traffic Collision Avoidance System aims to help aircraft to avoid collision with any object or other aircraft. One of the functions of this system is that it avoids threatening UAV to collide, it also addresses each threat separately with the best collision avoidance and the best suitable horizontal separation with other aircraft in the optimal path. In this paper the flight path planning for UAVs was designed to avoid obstacles depending on how the particle swarm was improved. Optimization problems are improved by using swarm dynamics (evolutionary computational technology). This is by describing avoiding obstacles and adapt the path planning for UAVs. The concept of concurrent restructuring has been integrated into path planning to stay away from both static obstacles. This optimization technique designed to decrease processing time and the shortest route of the path planning.