arXiv:2511.19691cs.RO2025-11

多智能体飞行安全框架,确保城市空中交通中编队飞行零碰撞。

Multi-Agent gatekeeper: Safe Flight Planning and Formation Control for Urban Air Mobility

  • 单个领航机预设安全路径,所有跟随机共享该路径作为应急备份。
  • 100次随机测试均零碰撞,显著优于基线方法的避障能力。
  • 适用于无人机编队飞行,尤其适合复杂城市三维环境。

我们提出多智能体门卫(Multi-Agent gatekeeper)框架,为复杂三维环境中领航-跟随编队控制提供可证明的安全保障。现有方法存在权衡:在线规划器缺乏形式化安全保证,离线规划器无法适应智能体数量或编队形态变化。为此,我们设计了一种混合架构:单一领航机跟踪预先计算的安全轨迹,该轨迹作为所有跟随机的共享安全备份路径。跟随机执行常规编队保持控制,并始终拥有沿领航机路径的已知安全应急机动方案,从而确保与静态障碍物及其他智能体的碰撞避免。我们正式证明该方法可实现无碰撞。主要贡献包括:(1) 将单智能体门卫框架扩展至多智能体系统;(2) 提出用于可证明安全协同的轨迹备份集;(3) 首次在三维环境中应用门卫框架。我们在模拟城市三维环境中验证方法,在100次随机试验中实现100%避障成功率,显著优于基线的CBF和NMPC方法。最后,我们在四旋翼无人机团队上验证了轨迹的物理可行性。

原文摘要 · Abstract (English)

We present Multi-Agent gatekeeper, a framework that provides provable safety guarantees for leader-follower formation control in cluttered 3D environments. Existing methods face a trad-off: online planners and controllers lack formal safety guarantees, while offline planners lack adaptability to changes in the number of agents or desired formation. To address this gap, we propose a hybrid architecture where a single leader tracks a pre-computed, safe trajectory, which serves as a shared trajectory backup set for all follower agents. Followers execute a nominal formation-keeping tracking controller, and are guaranteed to remain safe by always possessing a known-safe backup maneuver along the leader's path. We formally prove this method ensures collision avoidance with both static obstacles and other agents. The primary contributions are: (1) the multi-agent gatekeeper algorithm, which extends our single-agent gatekeeper framework to multi-agent systems; (2) the trajectory backup set for provably safe inter-agent coordination for leader-follower formation control; and (3) the first application of the gatekeeper framework in a 3D environment. We demonstrate our approach in a simulated 3D urban environment, where it achieved a 100% collision-avoidance success rate across 100 randomized trials, significantly outperforming baseline CBF and NMPC methods. Finally, we demonstrate the physical feasibility of the resulting trajectories on a team of quadcopters.

飞行规划多智能体安全控制无人机

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。