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基于视觉辅助导航的小旋翼机群编队穿越障碍技术 被引量:4

Heterogeneous Micro Air Vehicles Formation Crossing Obstacles Based on Vision-Aided Navigation
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摘要 该文基于单目视觉定位方法和LiDAR激光测高滤波算法,结合主−从式无人机编队策略,提出了一种低精度GPS条件下多传感器融合的小旋翼无人机编队穿越障碍技术。通过对该旋翼机编队系统的硬件架构、传感器分配、机载自组织网络以及机载编队地面站软件接口等关键模块的设计,最终搭建了一套完整的旋翼机编队测试平台。在完成视觉定位算法、激光数据时域滤波、ROS下编队飞行等仿真验证的基础上,进行了室外测试场地实机编队飞行测试,并利用该技术实现了对多组随机位置的门框类障碍的编队穿越、在线路径规划、一键式起飞返航等编队飞行任务,验证了该技术在室外复杂飞行环境中的可行性。 In this paper,a multi-sensor fusion technology for micro air vehicle formation crossing obstacles under low-precision GPS conditions is proposed based on the monocular vision positioning method,altimetry filter algorithm based on LiDAR,and the leading-following formation strategy of micro air vehicle.For verifying this technology,a complete set of the micro air vehicle formation test platform was established through the design of key modules such as the hardware architecture of the system,sensor distribution,airborne self-organizing network,and the software interface of the airborne formation ground station.The actual formation flying test of the outdoor test site was conducted on the base of the simulation verification of the visual positioning algorithm,time-domain filtering of laser data,and formation flying under the robot operating system.Finally,formation flying missions such as formation flying across multiple groups of door frame obstacles at random positions,online path planning,and one-key take-off and return were realized using this technology,verifying the feasibility of the technology in the outdoor complex flight environment.
作者 王梓豪 朱波 王奇 厚秉新 秦开宇 WANG Zi-Hao;ZHU Bo;WANG Qi;HOU Bing-Xin;QIN Kai-Yu(School of Aeronautics and Astronautics,University of Electronic Science and Technology of China,Chengdu,611731;School of Aeronautics and Astronautics,Sun Yat-sen University,Guangzhou,510006)
出处 《电子科技大学学报》 EI CAS CSCD 北大核心 2021年第3期391-397,共7页 Journal of University of Electronic Science and Technology of China
关键词 机载自组织网络 障碍穿越 激光雷达 小型旋翼机 单目视觉 传感器融合导航 airborne self-organized network crossing obstacles LiDAR micro air vehicle(MAV) monocular vision sensor data fusion
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