Multi-quadrotor systems face significant challenges in decentralized control, particularly with safety and coordination under sensing and communication limitations. State-of-the-art methods leverage Control Barrier Functions (CBFs) to provide safety guarantees but often neglect actuation constraints and limited detection range. To address these gaps, we propose a novel decentralized Nonlinear Model Predictive Control (NMPC) that integrates Exponential CBFs (ECBFs) to enhance safety and optimality in multi-quadrotor systems. We provide both conservative and practical minimum bounds of the range that preserve the safety guarantees of the ECBFs. We validate our approach through extensive simulations with up to 10 quadrotors and 20 obstacles, as well as real-world experiments with 3 quadrotors. Results demonstrate the effectiveness of the proposed framework in realistic settings, highlighting its potential for reliable quadrotor teams operations.

翻译：多旋翼无人机系统在分散式控制中面临重大挑战，特别是在传感与通信受限条件下的安全与协同问题。现有先进方法利用控制屏障函数（CBFs）提供安全性保证，但常忽略执行器约束与有限探测范围。为弥补这些不足，我们提出一种新颖的分散式非线性模型预测控制（NMPC）方法，该方法集成指数型控制屏障函数（ECBFs）以提升多旋翼无人机系统的安全性与最优性。我们给出了保持ECBFs安全性保证的探测范围保守最小界与实际最小界。通过包含多达10架无人机和20个障碍物的广泛仿真，以及3架无人机的实物实验，我们验证了所提方法的有效性。结果表明该框架在实际场景中具有显著效能，凸显了其在可靠多旋翼无人机编队运行中的应用潜力。