解决多无人机密集飞行时避撞约束冲突问题，提升系统可行性与安全性。
A Feasibility-Enhanced Control Barrier Function Method for Multi-UAV Collision Avoidance
- 引入符号一致性约束缓解多避撞约束内部不兼容性
- 在密集场景下使求解失败率显著降低，避撞成功率提升
- 适用于高密度无人机编队控制，适合实际飞行系统部署
本文提出一种可行性增强的控制屏障函数（FECBF）框架，用于多无人机（Multi-UAV）避撞。在密集多无人机场景中，由于多个控制屏障函数（CBF）约束之间存在内部不相容性，导致其二次规划（CBF-QP）求解常不可行。为此，本文分析了CBF约束的内部相容性，并推导出一个充分条件；基于该条件，引入符号一致性约束以缓解内部不相容问题。该约束被整合进使用最坏情况估计和松弛变量的分布式CBF-QP公式中。仿真结果表明，相比现有基线方法，该方法在密集场景下显著降低了不可行性并提升了避撞性能。不同时间延迟下的额外仿真验证了方法的鲁棒性。真实世界实验进一步证实了该方法的实际适用性。
原文摘要 · Abstract (English)
This paper presents a feasibility-enhanced control barrier function (FECBF) framework for multi-UAV collision avoidance. In dense multi-UAV scenarios, the feasibility of the CBF quadratic program (CBF-QP) can be compromised due to internal incompatibility among multiple CBF constraints. To address this issue, we analyze the internal compatibility of CBF constraints and derive a sufficient condition for internal compatibility. Based on this condition, a sign-consistency constraint is introduced to mitigate internal incompatibility. The proposed constraint is incorporated into a decentralized CBF-QP formulation using worst-case estimates and slack variables. Simulation results demonstrate that the proposed method significantly reduces infeasibility and improves collision avoidance performance compared with existing baselines in dense scenarios. Additional simulations under varying time delays demonstrate the robustness of the proposed method. Real-world experiments validate the practical applicability of the proposed method.
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