This paper describes a hierarchical solution consisting of a multi-phase planner and a low-level safe controller to jointly solve the safe navigation problem in crowded, dynamic, and uncertain environments. The planner employs dynamic gap analysis and trajectory optimization to achieve collision avoidance with respect to the predicted trajectories of dynamic agents within the sensing and planning horizon and with robustness to agent uncertainty. To address uncertainty over the planning horizon and real-time safety, a fast reactive safe set algorithm (SSA) is adopted, which monitors and modifies the unsafe control during trajectory tracking. Compared to other existing methods, our approach offers theoretical guarantees of safety and achieves collision-free navigation with higher probability in uncertain environments, as demonstrated in scenarios with 20 and 50 dynamic agents. Project website: https://hychen-naza.github.io/projects/HDAGap/.

翻译：本文提出一种由多阶段规划器与底层安全控制器组成的分层解决方案，以协同解决拥挤、动态及不确定环境中的安全导航问题。规划器通过动态间隙分析与轨迹优化，在感知与规划时域内实现与动态智能体预测轨迹的碰撞规避，并具备对智能体不确定性的鲁棒性。为应对规划时域的不确定性与实时安全需求，本文采用快速反应式安全集算法（SSA），该算法在轨迹跟踪过程中监控并修正不安全控制行为。相比现有方法，我们的方法具备理论安全保证，并在包含20和50个动态智能体的场景中验证了其在不稳定环境下实现更高概率无碰撞导航的能力。项目网站：https://hychen-naza.github.io/projects/HDAGap/。