文件名称:ukfslam
介绍说明--下载内容均来自于网络,请自行研究使用
采用ukf-SLAM算法对机器人和目标进行同步的定位-Ukf-SLAM algorithm using the robot and target position synchronized
(系统自动生成,下载前可以参看下载内容)
下载文件列表
ukfslam\add_control_noise.m
.......\add_observation_noise.m
.......\assert.m
.......\augment.m
.......\chi_square_bound.m
.......\chi_square_density.m
.......\chi_square_mass.m
.......\chi_square_to_gauss.m
.......\compute_steering.m
.......\configfile.m
.......\Contents.m
.......\covariance_intersection.m
.......\data_associate_known.m
.......\demo_bearing_only.m
.......\demo_chi_square.m
.......\demo_ekf_filter.m
.......\demo_kmeans.m
.......\demo_particle_filter.m
.......\demo_unscented_filter.m
.......\distance_bhattacharyya.m
.......\distance_KLD.m
.......\distance_KLD_symmetric.m
.......\distance_mahalanobis.m
.......\distance_normalised.m
.......\dist_sqr.m
.......\dist_sqr_.m
.......\dist_sqr_v2.m
.......\EKF_update.m
.......\ellipse_mass.m
.......\ellipse_sigma.m
.......\example_smallmap.mat
.......\example_webmap.mat
.......\gauss_entropy.m
.......\gauss_evaluate.m
.......\gauss_likelihood.m
.......\gauss_power.m
.......\gauss_regularise.m
.......\gauss_samples.m
.......\get_observations.m
.......\index_table.m
.......\inv_posdef.m
.......\inv_pseudo.m
.......\KF_update.m
.......\KF_update_cholesky.m
.......\KF_update_IEKF.m
.......\KF_update_joseph.m
.......\KF_update_simple.m
.......\kmeans.m
.......\line_plot_conversion.m
.......\multivariate_gauss.m
.......\numerical_Jacobian.m
.......\numerical_Jacobian_cd.m
.......\observe_heading.m
.......\observe_model.m
.......\pi_to_pi.m
.......\predict.asv
.......\predict.m
.......\readme.txt
.......\repcol.m
.......\reprow.m
.......\repvec.m
.......\sample_mean.m
.......\sample_mean_weighted.m
.......\sigma_ellipse.m
.......\sqrtm_2by2.m
.......\sqrt_posdef.m
.......\stratified_random.m
.......\stratified_resample.m
.......\transform_to_global.m
.......\transform_to_relative.m
.......\ukfslam_sim.m
.......\uniform_random.m
.......\unscented_transform.asv
.......\unscented_transform.m
.......\unscented_update.m
.......\update.m
.......\vehicle_model.m
ukfslam
.......\add_observation_noise.m
.......\assert.m
.......\augment.m
.......\chi_square_bound.m
.......\chi_square_density.m
.......\chi_square_mass.m
.......\chi_square_to_gauss.m
.......\compute_steering.m
.......\configfile.m
.......\Contents.m
.......\covariance_intersection.m
.......\data_associate_known.m
.......\demo_bearing_only.m
.......\demo_chi_square.m
.......\demo_ekf_filter.m
.......\demo_kmeans.m
.......\demo_particle_filter.m
.......\demo_unscented_filter.m
.......\distance_bhattacharyya.m
.......\distance_KLD.m
.......\distance_KLD_symmetric.m
.......\distance_mahalanobis.m
.......\distance_normalised.m
.......\dist_sqr.m
.......\dist_sqr_.m
.......\dist_sqr_v2.m
.......\EKF_update.m
.......\ellipse_mass.m
.......\ellipse_sigma.m
.......\example_smallmap.mat
.......\example_webmap.mat
.......\gauss_entropy.m
.......\gauss_evaluate.m
.......\gauss_likelihood.m
.......\gauss_power.m
.......\gauss_regularise.m
.......\gauss_samples.m
.......\get_observations.m
.......\index_table.m
.......\inv_posdef.m
.......\inv_pseudo.m
.......\KF_update.m
.......\KF_update_cholesky.m
.......\KF_update_IEKF.m
.......\KF_update_joseph.m
.......\KF_update_simple.m
.......\kmeans.m
.......\line_plot_conversion.m
.......\multivariate_gauss.m
.......\numerical_Jacobian.m
.......\numerical_Jacobian_cd.m
.......\observe_heading.m
.......\observe_model.m
.......\pi_to_pi.m
.......\predict.asv
.......\predict.m
.......\readme.txt
.......\repcol.m
.......\reprow.m
.......\repvec.m
.......\sample_mean.m
.......\sample_mean_weighted.m
.......\sigma_ellipse.m
.......\sqrtm_2by2.m
.......\sqrt_posdef.m
.......\stratified_random.m
.......\stratified_resample.m
.......\transform_to_global.m
.......\transform_to_relative.m
.......\ukfslam_sim.m
.......\uniform_random.m
.......\unscented_transform.asv
.......\unscented_transform.m
.......\unscented_update.m
.......\update.m
.......\vehicle_model.m
ukfslam