Slam2D is a project for optimizing a bundle adjustment problem in 2D-SLAM. It includes some source files and a test file named main.cpp in the folder demo. In the visual odemetry, a camera is restricted to moving in a 2D plane which is parallel to the landmark plane. Therefore, below parameters need to be optimized:

1. M landmarks(key points): X, Y (total number 2*M)
2. N camera pose(frames): x, y (total number 2*N)
3. camera intrinsic parameters: focal length, distortion
4. camera extrinsic parameters: rotation angle, Z(distance to landmark plane)

1. language: c++
2. platform: ubuntu 18.04
3. IDE: clion
4. compile: cmake, gcc
5. 3rd-party libraries: ceres(eigen3 needed)

1. bundle_adjustment.cpp It includes almost all key codes to accomplish bundle adjustment using ceres. A class named BundleAdjustment is defined in the file. During the class, below key functions are claimed:

1. Add observation
2. Compile(build the computational graph)
3. Solve(training procedure)
4. Report
5. Save model
6. Save PLY/PCL file to display meshlab/pcl etc.

2. model.cpp It is used to save/read model file and calculate position with new inputs.

The folder contains shared/static libraries generated after compiling source files.

The folder contains a demo program which shows how to use Slam2D.

The folder contains all outputs in the demo.

You can almost get started referring to main.cpp in the "demo" folder. Bellow are the main steps:

1. create an instance
2. add observations
3. compile
4. solve

Optional steps:

5. print report
6. save model
7. save PLY file(meshlab ./output/demo.ply to see the point cloud)

By the way, after compiling source files, you need not copy them but the shared-lib file to any other projects.