基于卡尔曼滤波器和迭代卡尔曼滤波器的SLAM附MATLAB代码+运行结果.zip

# islam_simulation The codes of the paper The Mobile Robot SLAM Simulation with Multi Measurement Update. If the paper is useful for you, please cite it. ``` @article{许亚芳2015基于多次测量更新的移动机器人SLAM仿真, title = {基于多次测量更新的移动机器人SLAM仿真}, author = {许亚芳 and 孙作雷 and 曾连荪 and 张波}, journal = {系统仿真学报}, year = {2015} } ``` # About the project Run the script "run.m", and you can see the demo of EKF-SLAM or IEKF-SLAM by setting the switches. Also, you can change the configurations and other switches in "run.m" to get different results. **Note:** Before run the script "run.m", you should set the path by hand. In the Matlab menu, just click Home->Set path->Add folder, and select the path of the file "IEKF and EKF Feature-based SLAM". **The following files mean :** ## Data Data about the robot surroundings and experiments. * **rollerCoaster.mat :** waypoints and landmarks. * **xTrue.mat :** ground truth. * **idList.mat :** corresponding list. * **ekfdata.mat :** experimental data of EKF-SLAM. * **iekfdata.mat :** experimental data of IEKF-SLAM. ## Filter It contains the filter codes for SLAM execution. * **main.m :** main loop of feature-based SLAM. * **predictEKF.m :** predict step of EKF and IEKF SLAM. * **updateEKF.m :** update step of EKF-SLAM. * **updateIEKF.m** and **iterate.m :** update step of IEKF-SLAM. * **augmentState.m :** augment step, that is add new features to the map. ## Models It contains all the models of filter. * **conNoise.m :** add random noise to control vector. * **vehicleModel.m :** generate ground truth and include motion model. * **obsModel.m :** observation model. ## Utilities Tools for SLAM Demo. * **compound.m :** complete the estimating uncertain spatial relationships in robotics. * **corresponding.m :** classify features with known corresponding. * **dataStore.m :** store online data. * **piTopi.m :** make sure the angle is in [-pi, pi]. ## Visualization Functions for animation. * **vis.m :** the main function for animation. * **getLandmark.m :** get the landmarks within robot's laser range. * **getSigmaEllipse.m :** for drawing the sigma ellipse which represents the uncertainty. * **makeFcov.m :** make features' covariance ecllipse. * **makeLines.m :** make sets of line segments for laser range-bearing measurements.