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空中操作机器人运动规划技术研究进展与展望(飞行器安全控制专刊)

张智星1,钟杭1,张彩霞1,梁嘉诚1,刘兰兰1,王耀南2   

  1. 1. 湖南大学
    2. 湖南大学电气与信息工程学院
  • 收稿日期:2026-01-21 修回日期:2026-03-31 出版日期:2026-04-02 发布日期:2026-04-02
  • 通讯作者: 王耀南
  • 基金资助:
    国家重大科研仪器研制项目;国家自然科学基金重点项目;江西省重点研发计划;江西省自然科学基金;装备状态感知与敏捷保障全国重点实验室基金;广东省基础与应用基础研究基金

Research progress and prospect of motion planning technology for aerial manipulators

  • Received:2026-01-21 Revised:2026-03-31 Online:2026-04-02 Published:2026-04-02
  • Supported by:
    National Natural Science Foundation of China;National Natural Science Foundation of China;Key R&D Program of JiangXi Province;National Natural Science Foundation of JiangXi Province;National Key Laboratory for Equipment Status Perception and Agile Support Fund;Guangdong Province Basic and Applied Basic Research Fund Project

摘要: 空中操作机器人通过与环境建立持续或瞬态的物理接触,从传统的信息获取平台拓展为具备主动作业能力的复杂交互系统,从“被动感知”向“主动作业”演进,在桥梁、电网、油气管道等大型能源交通基础设施的复杂交互场景中具有广阔应用前景。与非接触式飞行作业相比,接触式作业包含显著的动力学耦合、接触力限制及多模态运动切换,引入的高维非线性约束限制了运动规划的可行解空间,制约了系统的自主性与稳定性。针对上述挑战,本文系统综述了空中操作机器人运动规划领域的研究进展。首先,从系统架构出发,分析各类飞行平台构型以及作业机构对可规划空间与作业能力的影响;其次,总结了面向运动规划的系统建模方法,接触动力学建模与各类任务规划约束;在此基础上,围绕接触式作业任务的规划需求,分别介绍了基于采样、基于优化及基于学习的三类主流运动规划算法,分析其发展趋势,并比较其在高维状态搜索、动力学约束处理及实时重规划等方面的适用性与局限性。最后,总结了空中操作机器人面临的挑战并对未来发展趋势进行了展望。

关键词: 空中操作机器人, 旋翼飞行机器人, 运动规划, 接触式作业, 系统建模

Abstract: Abstract: Aerial manipulations expand from traditional information acquisition platforms into complex interactive systems with active operational capabilities by establishing continuous or transient physical contact with the environment. This evolution from "passive perception" to "active operation" demonstrates broad application prospects in complex interaction scenarios involving large-scale energy and transportation infrastructure, such as bridges, power grids, and oil and gas pipelines. Compared to non-contact flight missions, contact-based operations involve significant dynamic coupling, contact force constraints, and multi-modal motion switching. The resulting high-dimensional nonlinear constraints restrict the feasible solution space for motion planning, thereby constraining system autonomy and stability. To address these challenges, this paper provides a systematic review of research progress in the field of motion planning for aerial manipulations. First, starting from system architecture, we analyze the impact of various flight platform configurations and operational mechanisms (including tethered, rigid-linked, serial, and parallel structures) on the plannable space and operational capability. Second, we summarize system modeling methods oriented toward motion planning, including contact dynamics modeling and various task planning constraints. On this basis, centered on the planning requirements of contact-based tasks, three mainstream motion planning algorithms—sampling-based, optimization-based, and learning-based—are respectively introduced. Their development trends are analyzed, and their applicability and limitations in high-dimensional state search, dynamic constraint handling, and real-time replanning are compared. Finally, the challenges facing aerial manipulations are summarized, and future development trends are discussed.

Key words: Aerial manipulators, Multirotor aerial robots, Motion planning, Physical interaction, System modeling

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