视觉-惯性组合导航的无人机抗侧风纵向悬停水下基坑监测方法

Monitoring method of UAV anti crosswind longitudinal hovering underwater foundation pit based on vision inertial integrated navigation

摘要:

现有监测方法易受水下环境干扰、影响监测精度的问题,本研究创新性地提出了一种基于视觉-惯性组合导航的无人机抗侧风纵向悬停水下基坑监测方法。将经纬M300RTK高性能无人机作为空中平台,集成SHARE SLAM S10三维激光扫描仪与JZ_PT2缓降索投系统,并深度融合视觉-惯性组合导航技术与水下SLAM算法。通过采用水下复杂点云的区域生长体素滤波去噪算法,可有效提升点云质量。构建基于SLAM的实时位姿图优化函数,能够实现水下高精度定位与三维重建,进而建立全流程智能化监测预警体系。实验结果表明,该方法监测的坑口直径为1605mm、坑深为5505mm,监测结果与实验指标偏差仅5mm,垂直度误差最大值为0.005%,显著优于对比方法,并满足≤0.01%的指标要求,成功实现了“人员不上山、不下坑”的高精度、低风险水下基坑动态监测与预警,为深基坑工程安全管控提供了突破性的无人化、智能化解决方案。

Abstract:

The existing monitoring methods are vulnerable to the interference of underwater environment, which affects the monitoring accuracy. This research innovatively proposes a monitoring method of UAV anti crosswind longitudinal hovering underwater foundation pit based on vision inertial integrated navigation. The longitude latitude m300rtk high-performance UAV is used as the air platform, which integrates the share slam S10 3D laser scanner and jz714;pt2 slow descent cable delivery system, and deeply integrates the vision inertial integrated navigation technology and underwater SLAM algorithm. By using the region growing voxel filtering denoising algorithm of underwater complex point cloud, the quality of point cloud can be effectively improved. The real-time pose map optimization function based on slam can realize underwater high-precision positioning and three-dimensional reconstruction, and then establish the whole process intelligent monitoring and early warning system. The experimental results show that the diameter of the pit mouth monitored by this method is 1605mm, the depth of the pit is 5505mm, the deviation between the monitoring results and the experimental indicators is only 5mm, and the maximum Perpendicularity Error is 0.005%, which is significantly better than the comparison method, and meets the index requirements of ≤ 0.01%. It successfully realizes the high-precision, low-risk dynamic monitoring and early warning of underwater foundation pit, and provides a breakthrough unmanned and intelligent solution for the safety control of deep foundation pit engineering.