Predefined Location Formation: Keeping Control for UAV Clusters Based on Monte Carlo Strategy

作者：Shuzhen Li, Yuzhe Li, Junlin Zhu, Bin Liu · 发表于：Drones · 年份：2022 · DOI：10.3390/drones7010029 · 被引用次数：7 · 研究领域：Distributed Control Multi-Agent Systems、Robotic Path Planning Algorithms、UAV Applications and Optimization

UAV formation keeping is an important research element due to its cooperative formation control. This study proposes a passive positioning model for UAVs based on the Monte Carlo strategy and provides a trajectory programming decision scheme based on the predicted calculation of deviated UAV predefined endpoint locations, effectively improving the efficiency of UAVs performing formation-keeping tasks during flight. Then, the simulation after sampling by Gaussian distribution is used to obtain the trajectory planning under simultaneous control of multiple cluster formations, and the feasibility, accuracy and stability of the proposed model are verified. This study provides useful guidance for UAV formation control applications.