SLAM-用于SLAM的稀疏高斯过程实现-优质项目实战.zip

GP-SLAM Prerequisites ------ - CMake >= 2.6 (Ubuntu: `sudo apt-get install cmake`), compilation configuration tool. - [Boost](http://www.boost.org/) >= 1.46 (Ubuntu: `sudo apt-get install libboost-all-dev`), portable C++ source libraries. - [GTSAM](https://bitbucket.org/gtborg/gtsam) >= 4.0 alpha, a C++ library that implement smoothing and mapping (SAM) in robotics and vision. Compilation & Installation ------ In the library folder excute: ``` $ mkdir build $ cd build $ cmake .. $ make check # optonal, run unit tests $ make install ``` Matlab Toolbox ----- An optional Matlab toolbox is provided to use our library in Matlab. To enable Matlab toolbox during compilation: ``` $ cmake -DGPSLAM_BUILD_MATLAB_TOOLBOX:OPTION=ON -DGTSAM_TOOLBOX_INSTALL_PATH:PATH=/path/install/toolbox .. $ make install ``` After you install the Matlab toolbox, don't forget to add your `/path/install/toolbox` to your Matlab path. Compatibility ----- The GP-SLAM library is designed to be cross-platform, but it has been only tested on Ubuntu Linux for now. Tested Compilers: - GCC 4.8, 5.4 Tested Boost version: 1.48-1.61 Linking to External Projects ----- We provide easy linking to external **CMake** projects. Add following lines to your CMakeLists.txt ``` find_package(gpslam REQUIRED) include_directories(${gpslam_INCLUDE_DIR}) ```