基于时空解耦规划方法的无人机自主降落策略

徐扬; 魏超; 冯付勇; 胡乐云

doi:10.12382/bgxb.2024.0653

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基于时空解耦规划方法的无人机自主降落策略

更新时间：2025-09-05

- 基于时空解耦规划方法的无人机自主降落策略
- Autonomous Landing of UAVs based on Spatio-temporal Decomposition Planning
- 兵工学报 2025年46卷第7期页码：240653
- 作者机构：
  
  北京理工大学机械与车辆学院, 北京 100081
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2024.0653
  中图分类号：
- 收稿：2024-07-31，
  
  网络首发：2025-08-12，
  
  纸质出版：2025-07-31
- 稿件说明：
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徐扬, 魏超, 冯付勇, 等. 基于时空解耦规划方法的无人机自主降落策略[J]. 兵工学报, 2025,46(7):240653.

Yang XU, Chao WEI, Fuyong FENG, et al. Autonomous Landing of UAVs based on Spatio-temporal Decomposition Planning[J]. Acta Armamentarii, 2025, 46(7): 240653.
徐扬, 魏超, 冯付勇, 等. 基于时空解耦规划方法的无人机自主降落策略[J]. 兵工学报, 2025,46(7):240653. DOI： 10.12382/bgxb.2024.0653.

Yang XU, Chao WEI, Fuyong FENG, et al. Autonomous Landing of UAVs based on Spatio-temporal Decomposition Planning[J]. Acta Armamentarii, 2025, 46(7): 240653. DOI： 10.12382/bgxb.2024.0653.

摘要

空地协同系统中的无人车-无人机协同降落对拓展异构智能体集群的任务场景具有重要意义。目前基于轨迹优化的自主降落方法将时间与空间耦合在一起

通过设计最优控制律进行联合航迹优化

但存在优化目标函数设计较为复杂

无法发挥致动器最佳效能的问题。针对传统轨迹优化方法中时空维度过度耦合的问题

提出一种基于时空解耦的轨迹优化(Spatio-Temporal Decomposition Planning

STDP)方法

通过在空间与时间维度分别对降落轨迹进行优化

使无人机在复杂场景下采取更为激进的飞行策略。同时在设计目标函数时

综合考虑无人机的降落耗时以及电机功耗模型

以最优时间、能耗为控制目标构建2阶锥规划问题以加速求解

确保求解质量与效率。仿真结果表明

相较于时空耦合的规划方法

STDP方法规划出了更逼近运动学约束边界的轨迹

使得任务耗时大大缩减

提高了任务效率

同时实际场景中的测试结果也证明了STDP方法在实际应用中的可靠性。

Abstract

In air-ground collaborative systems

the coordinated landing of unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) is of paramount importance for extending the task scenarios of heterogeneous intelligent agent clusters.Current trajectory optimization-based autonomous landing methods couple the temporal and spatial dimensions by designing the optimal control laws for joint trajectory optimization.However

the optimization objective function design is relatively complex

and it cannot fully utilize the actuator’s optimal performance.A novel spatio-temporal decomposition planning (STDP) method is proposed to address the excessive coupling of time and space in traditional trajectory optimization methods.The STDP method optimizes the landing trajectories separately in spatial and temporal dimensions

enabling UAVs to adopt more aggressive flight strategies in complex scenarios.Furthermore

the objective function is meticulously designed to account for the UAV’s landing time and motor power consumption model

formulating a second-order cone programming problem to expedite the solution process while ensuring high-quality and efficient solutions.Simulated results indicate that

compared to spatio-temporal coupled planning methods

the STDP method generates the trajectories that closely adhere to kinematic constraints

substantially reducing the task completion time and enhancing the mission efficiency.Additionally

the empirical tests in real-world scenarios confirm the reliability and efficacy of STDP method in practical application.

关键词

Keywords

references

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