Author:xinliangzhong([email protected])
The package is used to calibrate a 2D LiDAR or laser range finder (LRF) with a monocular camera. Specficially, Hokuyo UTM-30LX have been suscessfully calibrated against a mono camera.
But this approach is really a naive way, in a word, it just 3D-2D optimization problem. So we decide to develop the new approach to calibrate the extrinsic
We have tested the library in 16.04, but it should be easy to compile in other platforms.
We use OpenCV to manipulate images and features. Dowload and install instructions can be found at: http://opencv.org. Required at leat 2.4.3. Tested with OpenCV 3.3.
Download and install instructions can be found at: http://eigen.tuxfamily.org. Required at least 3.1.0.
Download and install instructions can be found at: http://www.ceres-solver.org/installation.html.
mkdir build
cd build
cmake ..
make
We need the 3d points in laser coordination and the same points in the image.
The 3D points (actually z=0) you can put in the data/laser_points.txt;
The 2D points in the image you can put in the data/image_points.txt;
We combine the data in data.txt with 4 cols which represents x y u v respectively.
So how to fine the 3D-2D pairs correctly?
Here we provide a simple way:
Suppose your laser in the horizontal plane, and we just need to measure the height of the laser.
Actually the red point in the following picture is the flag that we tested in our setups.
For the x and y, you can use the rviz (2D nav goal) tool to measure. The result will be show in the terminal.
For the u and v in the image, we provide a simple tool to detect corners in the rectangle your mouse selected.
and the data will automatically saved in data/image_points.txt.
Actually it just a least square problem.
Tcl: which takes a vector from laser to camera.
