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引用次数: 0
摘要
目前的编队通常依赖于不变的层次结构,如预先确定的领导或列举的编队形状。这些结构可能是单向和迟缓的,在遇到杂乱环境时限制了它们的灵活性和敏捷性。为了克服这些限制,本研究提出了一种仿射编队的动态分层重组方法。我们的方法的核心是流畅的领导力和权力再分配,为此我们开发了一种由最短时间驱动的领导力评估算法和一种权力转换控制算法。这些算法有利于自主选择领导者,确保权力平稳过渡,使蜂群能够根据外部环境进行分层调整。大量的模拟和实际实验验证了所提方法的有效性。由五个空中机器人组成的编队成功地进行了动态分层重组,从而能够执行复杂的任务,如以高达 1.05 米/秒的速度进行转弯机动和环形导航。对比实验结果进一步证明了分层重组在提高编队灵活性和敏捷性方面的显著优势,尤其是在 U 形转弯等复杂机动过程中。值得注意的是,在上述真实世界的实验中,与没有进行分层重组的编队相比,所提出的方法至少减少了 33.8% 的飞行路径长度。
Flexible Affine Formation Control Based on Dynamic Hierarchical Reorganization
Current formations commonly rely on invariant hierarchical structures, such as predetermined leaders or enumerated formation shapes. These structures could be unidirectional and sluggish, constraining their flexibility and agility when encountering cluttered environments. To surmount these constraints, this work proposes a dynamic hierarchical reorganization approach with affine formation. Central to our approach is the fluid leadership and authority redistribution, for which we develop a minimum time-driven leadership evaluation algorithm and a power transition control algorithm. These algorithms facilitate autonomous leader selection and ensure smooth power transitions, enabling the swarm to adapt hierarchically in alignment with the external environment. Extensive simulations and real-world experiments validate the effectiveness of the proposed method. The formation of five aerial robots successfully performs dynamic hierarchical reorganizations, enabling the execution of complex tasks such as swerving maneuvers and navigating through hoops at velocities of up to 1.05m/s. Comparative experimental results further demonstrate the significant advantages of hierarchical reorganization in enhancing formation flexibility and agility, particularly during complex maneuvers such as U-turns. Notably, in the aforementioned real-world experiments, the proposed method reduces the flight path length by at least 33.8% compared to formations without hierarchical reorganization.
期刊介绍:
The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.