地下复杂空间无人机研究进展及其面临的挑战

Research progress and challenges faced by unmanned aerial vehicles in complex underground spaces

  • 摘要: 分析了地下复杂空间无人机的技术发展与应用现状,指出地下复杂空间无人机面临单体性能不足、环境态势感知与自主导航能力有限、编队协同能力有限等问题,针对上述问题,展望了地下无人机关键技术发展趋势:① 小型化轻量化一体化无人机设计技术。通过改进无人机的机械结构,提高激光雷达、深度相机等信息感知传感器与控制系统的集成度,优化电源管理系统等,最终实现单体无人机巡航速度、续航时间等性能的提升;② GPS拒止环境下态势感知与自主导航技术。攻克即时定位与地图构建(SLAM)导航与实时路径规划等关键技术难题,围绕特定场景逐步突破算法的局限性,提升无人系统的感知能力、环境适应性和鲁棒性;③ 有限信息下编队协同控制技术。攻克异构/同构无人机集群协同、复杂信道环境下的无线通信等技术难题,通过优化无人机群体智能控制策略、信息交互机制及任务决策协同机制等,增强集群无人系统的鲁棒性,提高无人系统在地下复杂环境中的自适应能力,进而提升无人系统的任务执行效率与成功率。

     

    Abstract: The technological development and application status of underground complex space UAVs are analyzed. It is pointed out that underground complex space UAVs face problems such as insufficient individual performance, limited environmental situational awareness and autonomous navigation capabilities, and limited formation collaboration capabilities. In order to solve the above problems, the development trends of key technologies for underground UAVs are prospected. ① Small and lightweight integrated UAV design technology is proposed. By improving the mechanical structure of the UAV, improving the integration of information perception sensors such as LiDAR and depth camera with control systems, and optimizing power management systems, the ultimate goal is to improve the cruise speed, endurance time, and other performance of individual UAV. ② Situation awareness and autonomous navigation technology in GPS rejection environment is proposed. The key technical challenges such as simultaneous localization and mapping (SLAM) navigation and real-time path planning should be overcome. The limitations of algorithms around specific scenarios should be gradually broken through. The perception capability, environmental adaptability, and robustness of unmanned systems should be improved. ③ Formation collaboration control technology under limited information is proposed. The technical problems such as heterogeneous/isomorphic UAV cluster collaboration, and wireless communication in complex channel environments should be overcome. By optimizing UAV swarm intelligence control strategies, information interaction mechanisms, and task decision-making collaboration mechanisms, the robustness of clustered unmanned systems should be enhanced. The adaptability of unmanned systems in complex underground environments should be improved. Furthermore, the task execution efficiency and success rate of unmanned systems should be improved.

     

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