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【背景】随着低空飞行活动的日益增多以及无人机系统故障率的居高不下，无人机系统具备高可靠性的应急着陆能力显得尤为重要。【目标】在复杂城市空域中，针对突发状况下多旋翼无人机的自主应急着陆安全性问题，提出一种在ICAROUS框架下面向应急决策的分层轨迹优化方法，旨在实现多旋翼无人机在应急情形下的高效自主安全着陆。【方法】该方法采用了高层路径规划与低层速度剖面相融合的优化模型。高层模块采用A*算法结合爬升代价以及飞行风险评估构建初始应急规划路径，并通过贝塞尔曲线进行平滑重构；低层优化环节引入马尔可夫决策过程(MDP)模型，构建路径段和速度的状态空间，以加速度为动作，设置合适的奖励函数和状态转移概率，采用值迭代算法求解最优速度剖面。【结论】仿真结果表明：相比于ICAROUS中的路径规划算法，提出的应急规划算法能在多个候选着陆点中权衡距离、风险与爬升代价，在风险维度上减小了28.8%，实现了风险可控的最优着陆点选择与路径生成；相比于SQP和PSO，本文提出方法所生成的速度剖面具有更佳的平滑性和能耗效率，并且飞行时间分别降低了10.7%与26.8%，平均速度波动均减少超过60%，有效提升了飞行安全性与能耗控制能力。【应用】该方法适用于多种城市低空飞行场景下的无人机应急规划，有效支持无人机在应急情形下的合理决策，可为城市空中交通管理系统中的飞行安全保障提供技术支撑。
Abstract：[Background] With the increase in the frequency of low-altitude flight activities and high failure rate of unmanned aerial vehicle(UAV) systems, ensuring high-reliability emergency landing capabilities has become crucial. [Objective] To address the safety challenges of autonomous emergency landing for multirotor UAVs in complex urban airspaces in unexpected scenarios, this study proposes a hierarchical trajectory optimization approach for emergency decision making within the ICAROUS framework, with the aim of achieving efficient, autonomous, and safe emergency landings. [Methods] The proposed approach adopts an integrated optimization model that combines highlevel path planning with low-level velocity profile optimization. At the high level, the A* algorithm is utilized along with climb cost and flight risk assessment to generate an initial emergency path, which is smoothed and reconstructed using Bézier curves. At the low level, a Markov decision process model is employed to define the state space based on path segments and velocities, with acceleration as the action. A suitable reward function and state transition probabilities are designed, and the optimal velocity profile is derived using the value iteration algorithm. [Conclusions] Simulation results show that, compared with the path planning algorithm in ICAROUS, the proposed emergency planning algorithm better balances the distance, risk, and climb cost among multiple candidate landing sites and reduces the risk metric by 28.8%. Furthermore, it selects the optimal landing point and generates paths with controllable risk. Compared with sequential quadratic programming and particle swarm optimization, the generated velocity profiles exhibit improved smoothness and energy efficiency with 10.7% and 26.8% lower flight times, respectively. The average velocity fluctuation reduces by more than 60%, thereby significantly enhancing the flight safety and energy management performance. [Applications] The proposed method can be applied to various low-altitude urban flight scenarios for UAV emergency planning. It effectively supports UAVs in making rational decisions under emergency conditions and provides technical support for flight safety assurance in urban air-traffic-management systems.
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基本信息:
DOI：10.19961/j.cnki.1672-4747.2025.06.019
中图分类号:V279;V249.1
引用信息:
[1]廖亿福,汤新民,顾俊伟等.ICAROUS框架下多旋翼无人机应急自主着陆轨迹优化[J].交通运输工程与信息学报,2025,23(03):115-129.DOI:10.19961/j.cnki.1672-4747.2025.06.019.
基金信息:
国家自然科学基金项目(52072174); 高端外国专家引进计划项目(G2023202003L); 天津市科技计划项目(24JCZDJC00090)