The invention provides an SLAM (Simultaneous Localization and Mapping) dynamic mapping method based on UAV (Unmanned Aerial Vehicle) vision, which is used for solving the technical problem of poor robustness of the existing SLAM dynamic mapping method. The method comprises the steps that a light and small unmanned aerial vehicle platform is built, a binocular camera sensor is carried at the front end of the unmanned aerial vehicle platform, an image of a scene around the unmanned aerial vehicle is obtained, and real-time SLAM mapping is carried out; processing the scene image around the unmanned aerial vehicle collected by the binocular camera sensor through a real-time dynamic target feature point detection algorithm, and detecting a dynamic object and a static object; and in combination with positioning information output by SLAM mapping, real-time semantic point cloud mapping in a dynamic environment is completed. According to the method, self-positioning is carried out while environment map construction is completed in an unknown environment by means of a binocular camera sensor, dynamic and static objects in a visual field are detected by using a YOLOv5 network and a multi-view geometric method, semantic point cloud mapping is carried out in combination with semantic information, and the method has the advantages of being small in size, low in cost, wide in application scene and accurate in positioning.
本发明提出了一种基于无人机视觉SLAM动态建图的方法,用以解决现有SLAM动态建图方法鲁棒性差的技术问题。本发明的步骤为:搭建轻小型无人机平台,在无人机平台前端搭载双目相机传感器,获取无人机周围场景图像,并进行实时SLAM建图;通过实时的动态目标特征点检测算法对双目相机传感器采集的无人机周围场景图像进行处理,检测动态物体和静态物体;结合SLAM建图输出的定位信息,完成动态环境下的实时语义点云建图。本发明依靠双目相机传感器在未知环境中完成环境地图构建同时进行自我定位,并利用YOLOv5网络和多视角几何方法对视野内的动静态物体检测,结合语义信息进行语义点云建图,具有体积小,成本低,适用场景广泛,且定位准确。
Dynamic mapping method based on visual SLAM (Simultaneous Localization and Mapping) of unmanned aerial vehicle
一种基于无人机视觉SLAM动态建图的方法
2024-05-07
Patent
Electronic Resource
Chinese
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