This paper presents a novel control method for a group of UAVs in obstacle-laden environments while preserving sensing network connectivity without data transmission between the UAVs. By leveraging constraints rooted in control barrier functions (CBFs), the proposed method aims to overcome the limitations, such as oscillatory behaviors and frequent constraint violations, of the existing method based on artificial potential fields (APFs). More specifically, the proposed method first determines desired control inputs by considering CBF-based constraints rather than repulsive APFs. The desired inputs are then minimally modified by solving a numerical optimization problem with soft constraints. In addition to the optimization-based method, we present an approximate method without numerical optimization. The effectiveness of the proposed methods is evaluated by extensive simulations to compare the performance of the CBF-based methods with an APF-based approach. Experimental results using real quadrotors are also presented.

翻译：本文提出了一种在障碍密集环境中保持无人机群感知网络连通性的新型控制方法，该方法无需无人机间的数据传输。通过利用基于控制屏障函数（CBFs）的约束条件，所提方法旨在克服现有基于人工势场（APFs）方法存在的振荡行为和频繁违反约束等局限性。具体而言，所提方法首先通过考虑基于CBF的约束而非排斥性APF来确定期望控制输入。随后，通过求解具有软约束的数值优化问题，对期望输入进行最小化修正。除基于优化的方法外，我们还提出了一种无需数值优化的近似方法。通过大量仿真实验，将基于CBF的方法与基于APF方法的性能进行对比，验证了所提方法的有效性。文中还展示了使用真实四旋翼飞行器的实验结果。