hku-mars / livox_camera_calib

This repository is used for automatic calibration between high resolution LiDAR and camera in targetless scenes.
GNU General Public License v2.0
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无法进入优化步骤,报错[pcl::KdTreeFLANN::setInputCloud] Cannot create a KDTree with an empty input cloud! #94

Open Goughhhhhh opened 1 year ago

Goughhhhhh commented 1 year ago

运行自己的录制的数据(Livox Avia录制的pcd点云和D4354i录制640×480分辨率的影像)时报错:[pcl::KdTreeFLANN::setInputCloud] Cannot create a KDTree with an empty input cloud! image 导致无法进入优化程序,具体表现为没有输出点云-图像残差图以及没有点云叠加的优化窗口,如下图所示: image image 排除了点云路径错误、点云话题名称错误以及点云密度过于稀疏等#19 Issue和#84 Issue中提到的可能的错误,即能读取并在rviz上显示就说明点云路径和话题名称没错,能提取到足够多的线特征(红色的线条)就说明点云密度达到标定要求(为此我还对比了项目demo中3.pcd的点云密度,我采集的点云数量远高于demo中的点云数量),如下图所示。但是问题依然没有得到解决。 image 当我把D435i的影像分辨率改为和作者demo中提供的影像分辨率1920×1080,并在相同环境、相同位置录制数据后,程序正常运行了!请问作者和各位大佬们,这可能是什么问题?如果想用640×480分辨率的影像进行标定,我该怎么做? 回复为盼。祝大家好!

tdcsu commented 9 months ago

First, I fixed the livox avia at a certain location,
then I ran the fast_lio to get a denser registration of pointcloud.
At the same time, the images from a sub_cam with resolution 640x480 were recored. After that, I ran the calibration based on the last frame image and the cloud registration, and successfully get a not bad result.

As you can see from the figures below, the topleft is the color_pcd, the bottom is the cloud regidtration by fast_lio based on livox avia, and the right is the image from usb_cam. cali Here is my senser setup: 87e5c2c0803782741ad0c109ad8733a

tdcsu commented 9 months ago

First, I fixed the livox avia at a certain location, then I ran the fast_lio to get a denser registration of pointcloud. At the same time, the images from a sub_cam with resolution 640x480 were recored. After that, I ran the calibration based on the last frame image and the cloud registration, and successfully get a not bad result.

As you can see from the figures below, the topleft is the color_pcd, the bottom is the cloud regidtration by fast_lio based on livox avia, and the right is the image from usb_cam. cali cali Here is my senser setup: 87e5c2c0803782741ad0c109ad8733a

so i think if the density of your point cloud is not enough.