SLAM algorithm based on the EKF-SLAM algorithm and the surrounding environment movement to synchronize the robot to locate and identify the simulation environment, you can achieve high positioning accuracy and the results

ekfslam_v1.0\add_control_noise.m
............\add_observation_noise.m
............\augment.asv
............\augment.m
............\augment_associate_known.m
............\compute_steering.m
............\configfile.m
............\data_associate.m
............\data_associate_known.m
............\ekfslam_sim.asv
............\ekfslam_sim.m
............\example_densemap.mat
............\example_webmap.mat
............\frontend.fig
............\frontend.m
............\get_observations.m
............\KF_cholesky_update.m
............\KF_IEKF_update.m
............\KF_simple_update.m
............\line_plot_conversion.m
............\observe_heading.m
............\observe_model.asv
............\observe_model.m
............\pi_to_pi.m
............\plot_feature_loci.m
............\predict.asv
............\predict.m
............\readme.txt
............\TransformToGlobal.m
............\update.m
............\update_iekf.m
............\vehicle_model.m
ekfslam_v1.0

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