├── .kdev4 └── particle_filter_localization.kdev4 ├── CMakeLists.txt ├── LICENSE ├── README.md ├── config └── default.yaml ├── include └── particle_filter_localization │ ├── Pose2d.h │ ├── grid_map.h │ ├── localizer.h │ ├── measurement_model.h │ ├── motion_model.h │ ├── particle.h │ └── robot.h ├── launch └── pf_localization.launch ├── map └── map.png ├── package.xml ├── particle_filter_localization.kdev4 ├── rviz └── default.rviz ├── src ├── grid_map.cc ├── localizer.cc ├── measurement_model.cc └── motion_model.cc └── test ├── odometry.cc └── pf_localization_node.cc /.kdev4/particle_filter_localization.kdev4: -------------------------------------------------------------------------------- 1 | [Buildset] 2 | BuildItems=@Variant(\x00\x00\x00\t\x00\x00\x00\x00\x01\x00\x00\x00\x0b\x00\x00\x00\x00\x01\x00\x00\x008\x00p\x00a\x00r\x00t\x00i\x00c\x00l\x00e\x00_\x00f\x00i\x00l\x00t\x00e\x00r\x00_\x00l\x00o\x00c\x00a\x00l\x00i\x00z\x00a\x00t\x00i\x00o\x00n) 3 | 4 | [CMake] 5 | Build Directory Count=1 6 | Current Build Directory Index=0 7 | ProjectRootRelative= 8 | 9 | [CMake][CMake Build Directory 0] 10 | Build Directory Path=file:///home/yds/catkin_ws/build/particle_filter_localization 11 | Build Type=Release 12 | CMake Binary=file:///usr/bin/cmake 13 | Environment Profile= 14 | Extra Arguments=-DCATKIN_DEVEL_PREFIX=../../devel -DCMAKE_INSTALL_PREFIX=../../install 15 | Install Directory=file:///home/yds/catkin_ws/install 16 | 17 | [Defines And Includes][Compiler] 18 | Name=GCC 19 | Path=gcc 20 | Type=GCC 21 | -------------------------------------------------------------------------------- /CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 2.8.3) 2 | project(particle_filter_localization) 3 | 4 | ## Compile as C++11, supported in ROS Kinetic and newer 5 | add_compile_options(-std=c++11) 6 | set(CMAKE_BUILD_TYPE Release) 7 | 8 | ## Find catkin macros and libraries 9 | find_package(catkin REQUIRED COMPONENTS 10 | roscpp 11 | cv_bridge 12 | geometry_msgs 13 | nav_msgs 14 | sensor_msgs 15 | std_msgs 16 | tf 17 | pcl_ros 18 | ) 19 | 20 | 21 | catkin_package( 22 | ) 23 | 24 | find_package(OpenCV 3.0 QUIET) 25 | find_package(Eigen3 REQUIRED) 26 | 27 | include_directories( 28 | ${catkin_INCLUDE_DIRS} 29 | ${PROJECT_SOURCE_DIR} 30 | ${PROJECT_SOURCE_DIR}/include 31 | ${EIGEN3_INCLUDE_DIR} 32 | ${PCL_INCLUDE_DIRS} 33 | ) 34 | 35 | add_library(${PROJECT_NAME} SHARED 36 | src/grid_map.cc 37 | src/motion_model.cc 38 | src/measurement_model.cc 39 | src/localizer.cc 40 | ) 41 | 42 | target_link_libraries(${PROJECT_NAME} 43 | ${catkin_LIBRARIES} 44 | ${OpenCV_LIBS} 45 | ${EIGEN3_LIBS} 46 | ${PCL_LIBRARIES} 47 | ) 48 | 49 | 50 | add_executable(odometry 51 | test/odometry.cc) 52 | target_link_libraries(odometry 53 | ${catkin_LIBRARIES} 54 | ${PROJECT_NAME} 55 | ) 56 | 57 | 58 | add_executable(pf_localization_node 59 | test/pf_localization_node.cc) 60 | target_link_libraries(pf_localization_node 61 | ${catkin_LIBRARIES} 62 | ${PROJECT_NAME} 63 | ) -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | # Particle Filter Localization 3 | ## Particle filter-based localization in an occupancy grid map. 4 | 5 | For details, please refer to：https://zhuanlan.zhihu.com/p/43523632 6 | 7 | Dataset：https://pan.baidu.com/s/1j_SSEtaq7D0XwaED0Jg4Ew 8 | 9 | ## Demo 10 | 11 | STEP1. Download the repository to your ROS workspace：catkin_ws/src 12 | 13 | STEP2. Make：catkin_make 14 | 15 | STEP3. Run: roslaunch particle_filter_localization pf_localization.launch 16 | 17 | STEP4. Play a rosbag: rosbag play laser1_2018-07-14-17-31-41.bag -r 2 18 | -------------------------------------------------------------------------------- /config/default.yaml: -------------------------------------------------------------------------------- 1 | 2 | map: 3 | sizex: 1000 4 | sizey: 1000 5 | initx: 386 6 | inity: 386 7 | cell_size: 0.05 8 | frame_id: odom 9 | 10 | sensor_model: 11 | P_occ: 0.6 12 | P_free: 0.4 13 | P_prior: 0.5 14 | 15 | robot: 16 | kl: 2.31249273072714e-06 17 | kr: 2.30439760302837e-06 18 | b: 0.719561485930414 19 | 20 | robot_laser: 21 | x: 0.26 22 | y: 0.0 23 | theta: 0.0 24 | 25 | motion_model: 26 | alpha1: 0.15 27 | alpha2: 0.15 28 | alpha3: 0.15 29 | alpha4: 0.15 30 | 31 | measurement_model: 32 | sigma: 0.2 33 | rand: 0.01 34 | 35 | particle_filter: 36 | n_particles: 1000 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | -------------------------------------------------------------------------------- /include/particle_filter_localization/Pose2d.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef POSE2D_H 5 | #define POSE2D_H 6 | 7 | #include 8 | #define PI 3.1415926 9 | 10 | class Pose2d{ 11 | public: 12 | Pose2d(){ 13 | x_ = 0.0; 14 | y_ = 0.0; 15 | theta_ = 0.0; 16 | } 17 | Pose2d(double x, double y, double theta):x_(x), y_(y), theta_(theta){} 18 | 19 | const Pose2d operator*(const Pose2d& p2) 20 | { 21 | Pose2d p; 22 | Eigen::Matrix2d R; 23 | R << cos(theta_), -sin(theta_), 24 | sin(theta_), cos(theta_); 25 | Eigen::Vector2d pt2(p2.x_, p2.y_); 26 | Eigen::Vector2d pt = R * pt2 + Eigen::Vector2d(x_, y_); 27 | 28 | p.x_ = pt(0); 29 | p.y_ = pt(1); 30 | p.theta_ = theta_ + p2.theta_; 31 | NormAngle( p.theta_); 32 | return p; 33 | } 34 | 35 | const Eigen::Vector2d operator*(const Eigen::Vector2d& p) 36 | { 37 | Eigen::Matrix2d R; 38 | R << cos(theta_), -sin(theta_), 39 | sin(theta_), cos(theta_); 40 | Eigen::Vector2d t(x_, y_); 41 | return R * p + t; 42 | } 43 | 44 | 45 | Pose2d inv() 46 | { 47 | double x = -( cos(theta_) * x_ + sin(theta_) * y_); 48 | double y = -( -sin(theta_) * x_ + cos(theta_) * y_); 49 | double theta = -theta_; 50 | return Pose2d(x, y, theta); 51 | } 52 | 53 | static void NormAngle ( double& angle ) 54 | { if( angle >= PI) 55 | angle -= 2.0*PI; 56 | if( angle < -PI) 57 | angle += 2.0*PI; 58 | } 59 | double x_, y_, theta_; 60 | }; //class Pose2d 61 | 62 | 63 | #endif 64 | 65 | -------------------------------------------------------------------------------- /include/particle_filter_localization/grid_map.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef GRID_MAP_H 5 | #define GRID_MAP_H 6 | 7 | #include 8 | #include 9 | #include 10 | 11 | 12 | 13 | class GridMap{ 14 | public: 15 | GridMap(){} 16 | GridMap(const int& size_x, const int& size_y, const int& init_x, const int& init_y, const double& cell_size ); 17 | bool setGridBel(const double& x, const double& y, const double& bel); 18 | bool getGridBel ( const double& x, const double& y, double& bel); 19 | bool setGridLogBel(const double& x, const double& y, const double& log_bel); 20 | bool getGridLogBel(const double& x, const double& y, double& log_bel); 21 | double getCellSize(); 22 | double minX(); 23 | double maxX(); 24 | double minY(); 25 | double maxY(); 26 | 27 | void toRosOccGridMap(const std::string& frame_id, nav_msgs::OccupancyGrid& occ_grid); //转换到Ros栅格地图的消息 28 | cv::Mat toCvMat(); //转换到Opencv的图片格式 29 | void saveMap(const std::string& img_dir, const std::string& cfg_dir); // 保存地图，图片加配置文件的形式 30 | void loadMap(const std::string& img_dir, const std::string& cfg_dir); // TODO 加载地图 31 | void loadMap(const std::string& img_dir, const int& init_x, const int& init_y, const double& cell_size); 32 | 33 | 34 | 35 | bool getIdx(const double& x, const double& y, Eigen::Vector2i& idx); 36 | int size_x_, size_y_, init_x_, init_y_; 37 | double cell_size_; 38 | Eigen::MatrixXd bel_data_; 39 | Eigen::MatrixXd m_one_, m_show_; 40 | 41 | };// class GridMap 42 | 43 | 44 | #endif -------------------------------------------------------------------------------- /include/particle_filter_localization/localizer.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef LOCALIZER_H 5 | #define LOCALIZER_H 6 | 7 | #include 8 | #include 9 | #include 10 | #include 11 | #include 12 | 13 | #include 14 | #include 15 | 16 | class Localizer{ 17 | public: 18 | Localizer(Robot* robot, GridMap* map, MotionModel* motion_model, MeasurementModel* measurement_model, size_t nParticles); 19 | void motionUpdate(const Pose2d& odom); 20 | void measurementUpdate(const sensor_msgs::LaserScanConstPtr& scan ); 21 | void reSample(); 22 | void particles2RosPoseArray(geometry_msgs::PoseArray& pose_array); 23 | void normalization(); 24 | 25 | private: 26 | Robot* robot_; 27 | GridMap* map_; 28 | MotionModel* motion_model_; 29 | MeasurementModel* measurement_model_; 30 | 31 | size_t nParticles_; 32 | std::vector particles_; //粒子 33 | 34 | /* sys statues */ 35 | bool is_init_; 36 | Pose2d last_odom_pose_; 37 | }; //class Localizer 38 | 39 | #endif 40 | 41 | -------------------------------------------------------------------------------- /include/particle_filter_localization/measurement_model.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef MEASUREMENT_MODEL 5 | #define MEASUREMENT_MODEL 6 | 7 | #include 8 | #include 9 | 10 | class MeasurementModel{ 11 | public: 12 | MeasurementModel(GridMap* map, const double& sigma, const double& rand); 13 | double likelihoodFieldRangFinderModel(const double& x, const double& y); 14 | 15 | bool getIdx(const double& x, const double& y, Eigen::Vector2i& idx); 16 | bool setGridLikelihood(const double& x, const double& y, const double& likelihood); 17 | double getGridLikelihood ( const double& x, const double& y); 18 | cv::Mat toCvMat(); //转换到Opencv的图片格式 19 | private: 20 | double gaussion(const double& mu, const double& sigma, double x); 21 | 22 | GridMap* map_; 23 | double sigma_; 24 | double rand_; 25 | 26 | pcl::KdTreeFLANN kd_tree_; 27 | 28 | /* 预先计算似然域的数据 */ 29 | Eigen::MatrixXd likelihood_data_; 30 | int size_x_, size_y_, init_x_, init_y_; 31 | double cell_size_; 32 | 33 | 34 | }; //class MeasurementModel 35 | 36 | #endif 37 | 38 | 39 | -------------------------------------------------------------------------------- /include/particle_filter_localization/motion_model.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef MOTION_MODEL_H 5 | #define MOTION_MODEL_H 6 | #include 7 | #include 8 | 9 | class MotionModel{ 10 | public: 11 | MotionModel(const double& alpha1, const double& alpha2, const double& alpha3, const double& alpha4); 12 | void sampleMotionModelOdometry(const double& delta_rot1, const double& delta_trans, const double& delta_rot2, Pose2d& xt); 13 | 14 | private: 15 | double alpha1_, alpha2_, alpha3_, alpha4_; 16 | cv::RNG rng_; 17 | }; // class MotionModel 18 | 19 | 20 | #endif 21 | -------------------------------------------------------------------------------- /include/particle_filter_localization/particle.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef PARTICLE_H 5 | #define PARTICLE_H 6 | 7 | #include 8 | 9 | class Particle{ 10 | public: 11 | Particle(Pose2d pose, long double weight): pose_(pose), weight_(weight){} 12 | public: 13 | Pose2d pose_; 14 | long double weight_; 15 | }; 16 | 17 | #endif 18 | 19 | -------------------------------------------------------------------------------- /include/particle_filter_localization/robot.h: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #ifndef ROBOT_H 5 | #define ROBOT_H 6 | 7 | #include 8 | 9 | class Robot{ 10 | public: 11 | Robot(const double& kl, const double& kr, const double& b, const Pose2d& T_r_l): 12 | kl_(kl), kr_(kr), b_(b), T_r_l_(T_r_l) 13 | {} 14 | 15 | double kl_, kr_, b_; 16 | Pose2d T_r_l_; 17 | };//class Robot 18 | 19 | #endif 20 | 21 | -------------------------------------------------------------------------------- /launch/pf_localization.launch: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 14 | 15 | 16 | -------------------------------------------------------------------------------- /map/map.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ydsf16/particle_filter_localization/f742315d9cd54fc1367622d1dd1161906c4c2094/map/map.png -------------------------------------------------------------------------------- /package.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | particle_filter_localization 4 | 0.0.0 5 | The particle_filter_localization package 6 | 7 | 8 | 9 | 10 | yds 11 | 12 | 13 | 14 | 15 | 16 | TODO 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | 49 | 50 | 51 | catkin 52 | roscpp 53 | roscpp 54 | roscpp 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 | 63 | -------------------------------------------------------------------------------- /particle_filter_localization.kdev4: -------------------------------------------------------------------------------- 1 | [Project] 2 | Manager=KDevCMakeManager 3 | Name=particle_filter_localization 4 | -------------------------------------------------------------------------------- /rviz/default.rviz: -------------------------------------------------------------------------------- 1 | Panels: 2 | - Class: rviz/Displays 3 | Help Height: 0 4 | Name: Displays 5 | Property Tree Widget: 6 | Expanded: 7 | - /Odometry1/Shape1 8 | - /PoseArray1 9 | Splitter Ratio: 0.5 10 | Tree Height: 440 11 | - Class: rviz/Selection 12 | Name: Selection 13 | - Class: rviz/Tool Properties 14 | Expanded: 15 | - /2D Pose Estimate1 16 | - /2D Nav Goal1 17 | - /Publish Point1 18 | Name: Tool Properties 19 | Splitter Ratio: 0.588679016 20 | - Class: rviz/Views 21 | Expanded: 22 | - /Current View1 23 | Name: Views 24 | Splitter Ratio: 0.5 25 | - Class: rviz/Time 26 | Experimental: false 27 | Name: Time 28 | SyncMode: 0 29 | SyncSource: "" 30 | Visualization Manager: 31 | Class: "" 32 | Displays: 33 | - Alpha: 0.200000003 34 | Cell Size: 1 35 | Class: rviz/Grid 36 | Color: 255; 255; 255 37 | Enabled: false 38 | Line Style: 39 | Line Width: 0.0299999993 40 | Value: Billboards 41 | Name: Grid 42 | Normal Cell Count: 0 43 | Offset: 44 | X: 0 45 | Y: 0 46 | Z: 0 47 | Plane: XY 48 | Plane Cell Count: 50 49 | Reference Frame: 50 | Value: false 51 | - Angle Tolerance: 0.0500000007 52 | Class: rviz/Odometry 53 | Covariance: 54 | Orientation: 55 | Alpha: 0.5 56 | Color: 255; 255; 127 57 | Color Style: Unique 58 | Frame: Local 59 | Offset: 1 60 | Scale: 1 61 | Value: true 62 | Position: 63 | Alpha: 0.300000012 64 | Color: 204; 51; 204 65 | Scale: 1 66 | Value: true 67 | Value: true 68 | Enabled: false 69 | Keep: 10000 70 | Name: Odometry 71 | Position Tolerance: 0.100000001 72 | Shape: 73 | Alpha: 1 74 | Axes Length: 0.100000001 75 | Axes Radius: 0.0500000007 76 | Color: 255; 25; 0 77 | Head Length: 0.300000012 78 | Head Radius: 0.100000001 79 | Shaft Length: 1 80 | Shaft Radius: 0.0500000007 81 | Value: Axes 82 | Topic: /mbot/odometry 83 | Unreliable: false 84 | Value: false 85 | - Alpha: 0.699999988 86 | Class: rviz/Map 87 | Color Scheme: map 88 | Draw Behind: false 89 | Enabled: true 90 | Name: Map 91 | Topic: /pf_localization/grid_map 92 | Unreliable: false 93 | Use Timestamp: false 94 | Value: true 95 | - Alpha: 1 96 | Arrow Length: 0.300000012 97 | Axes Length: 0.400000006 98 | Axes Radius: 0.0299999993 99 | Class: rviz/PoseArray 100 | Color: 255; 25; 0 101 | Enabled: true 102 | Head Length: 0.0700000003 103 | Head Radius: 0.0299999993 104 | Name: PoseArray 105 | Shaft Length: 0.230000004 106 | Shaft Radius: 0.00999999978 107 | Shape: Arrow (Flat) 108 | Topic: /pf_localization/particles 109 | Unreliable: false 110 | Value: true 111 | Enabled: true 112 | Global Options: 113 | Background Color: 40; 40; 40 114 | Default Light: true 115 | Fixed Frame: odom 116 | Frame Rate: 30 117 | Name: root 118 | Tools: 119 | - Class: rviz/Interact 120 | Hide Inactive Objects: true 121 | - Class: rviz/MoveCamera 122 | - Class: rviz/Select 123 | - Class: rviz/FocusCamera 124 | - Class: rviz/Measure 125 | - Class: rviz/SetInitialPose 126 | Topic: /initialpose 127 | - Class: rviz/SetGoal 128 | Topic: /move_base_simple/goal 129 | - Class: rviz/PublishPoint 130 | Single click: true 131 | Topic: /clicked_point 132 | Value: true 133 | Views: 134 | Current: 135 | Angle: -6.2650156 136 | Class: rviz/TopDownOrtho 137 | Enable Stereo Rendering: 138 | Stereo Eye Separation: 0.0599999987 139 | Stereo Focal Distance: 1 140 | Swap Stereo Eyes: false 141 | Value: false 142 | Invert Z Axis: false 143 | Name: Current View 144 | Near Clip Distance: 0.00999999978 145 | Scale: 25.4194641 146 | Target Frame: 147 | Value: TopDownOrtho (rviz) 148 | X: -3.03675699 149 | Y: -0.856096983 150 | Saved: ~ 151 | Window Geometry: 152 | Displays: 153 | collapsed: true 154 | Height: 1056 155 | Hide Left Dock: true 156 | Hide Right Dock: true 157 | QMainWindow State: 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 158 | Selection: 159 | collapsed: false 160 | Time: 161 | collapsed: false 162 | Tool Properties: 163 | collapsed: false 164 | Views: 165 | collapsed: true 166 | Width: 1855 167 | X: 65 168 | Y: 24 169 | -------------------------------------------------------------------------------- /src/grid_map.cc: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #include 5 | 6 | GridMap::GridMap ( const int& size_x, const int& size_y, const int& init_x, const int& init_y, const double& cell_size ) : 7 | size_x_ ( size_x ), size_y_ ( size_y ), init_x_ ( init_x ), init_y_ ( init_y ), cell_size_ ( cell_size ) 8 | { 9 | bel_data_.resize ( size_x_, size_y_ ); 10 | bel_data_.setOnes() *= 0.5; //全部设为0.5的概率 11 | 12 | /* 为opencv图片显示相关 */ 13 | m_one_.resize(size_x_, size_y_); 14 | m_one_.setOnes(); 15 | m_show_.resize(size_x_, size_y_); 16 | m_show_.setOnes() * 0.5; 17 | } 18 | 19 | bool GridMap::getIdx ( const double& x, const double& y, Eigen::Vector2i& idx ) 20 | { 21 | int xidx = cvFloor( x / cell_size_ ) + init_x_; 22 | int yidx = cvFloor( y /cell_size_ )+ init_y_; 23 | 24 | // TODO 动态扩张地图 25 | if((xidx < 0) || (yidx < 0) || (xidx >= size_x_) || (yidx >= size_y_)) 26 | return false; 27 | idx << xidx , yidx; 28 | return true; 29 | } 30 | 31 | bool GridMap::getGridBel ( const double& x, const double& y, double& bel) 32 | { 33 | Eigen::Vector2i idx; 34 | if(!getIdx(x, y, idx)) 35 | return false; 36 | bel = bel_data_(idx(0), idx(1)); 37 | return true; 38 | } 39 | 40 | bool GridMap::setGridBel ( const double& x, const double& y, const double& bel ) 41 | { 42 | Eigen::Vector2i idx; 43 | if(!getIdx(x, y, idx)) 44 | return false; 45 | bel_data_(idx(0), idx(1)) = bel; 46 | return true; 47 | } 48 | 49 | bool GridMap::getGridLogBel ( const double& x, const double& y, double& log_bel ) 50 | { 51 | double bel; 52 | if(!getGridBel(x, y, bel)) 53 | return false; 54 | log_bel = log( bel / (1.0-bel)); 55 | return true; 56 | } 57 | 58 | bool GridMap::setGridLogBel ( const double& x, const double& y, const double& log_bel ) 59 | { 60 | double bel = 1.0 - 1.0 / (1 + exp(log_bel)); 61 | if( !setGridBel(x, y, bel) ) 62 | return false; 63 | return true; 64 | } 65 | 66 | double GridMap::getCellSize() 67 | { 68 | return cell_size_; 69 | } 70 | 71 | double GridMap::minX() 72 | { 73 | return (0 - init_x_) * cell_size_; 74 | } 75 | 76 | double GridMap::maxX() 77 | { 78 | return (size_x_ - init_x_) * cell_size_; 79 | } 80 | 81 | double GridMap::minY() 82 | { 83 | return (0 - init_y_) * cell_size_; 84 | } 85 | 86 | double GridMap::maxY() 87 | { 88 | return (size_y_ - init_y_) * cell_size_; 89 | } 90 | 91 | 92 | 93 | 94 | cv::Mat GridMap::toCvMat() 95 | { 96 | /* 构造opencv mat */ 97 | m_show_ = m_one_ - bel_data_; //翻转数值 98 | /* 构造出opencv格式显示 */ 99 | cv::Mat map(cv::Size(size_x_, size_y_), CV_64FC1, m_show_.data(), cv::Mat::AUTO_STEP); 100 | /* 翻转 */ 101 | cv::flip(map, map, 0); 102 | 103 | return map; 104 | } 105 | 106 | void GridMap::toRosOccGridMap( const std::string& frame_id, nav_msgs::OccupancyGrid& occ_grid) 107 | { 108 | occ_grid.header.frame_id = frame_id; 109 | occ_grid.header.stamp = ros::Time::now(); 110 | 111 | occ_grid.info.width = size_x_; 112 | occ_grid.info.height = size_y_; 113 | occ_grid.info.resolution = cell_size_; 114 | occ_grid.info.origin.position.x = -init_x_*cell_size_; 115 | occ_grid.info.origin.position.y = -init_y_*cell_size_; 116 | 117 | const int N = size_x_ * size_y_; 118 | for(size_t i= 0; i < N; i ++) 119 | { 120 | double& value = bel_data_.data()[i]; 121 | if(value == 0.5) 122 | occ_grid.data.push_back( -1); 123 | else 124 | occ_grid.data.push_back( value * 100); 125 | } 126 | } 127 | 128 | 129 | void GridMap::saveMap ( const std::string& img_dir, const std::string& cfg_dir ) 130 | { 131 | /* 保存图片 */ 132 | cv::Mat img = toCvMat(); 133 | img = img * 255; 134 | cv::imwrite(img_dir, img); 135 | 136 | /* 保存配置 */ 137 | std::ofstream file; 138 | file.open(cfg_dir); 139 | file << "map:"<< std::endl 140 | << " size_x: " << size_x_ << std::endl 141 | << " size_y: " << size_y_ << std::endl 142 | << " init_x: " << init_x_ << std::endl 143 | << " init_y: " << init_y_ << std::endl 144 | << " cell_size: " << cell_size_ << std::endl; 145 | } 146 | 147 | // TODO 148 | void GridMap::loadMap ( const std::string& img_dir, const std::string& cfg_dir ) 149 | { 150 | /* 利用opencv读取地图图片 */ 151 | cv::Mat cv_map = cv::imread(img_dir); 152 | cv::imshow("map", cv_map); 153 | cv::waitKey(0); 154 | 155 | /* 转换成灰度格式 */ 156 | 157 | 158 | /* 根据阈值加载到Eigen形式 */ 159 | 160 | 161 | /* 构造 K-D 树 */ 162 | 163 | 164 | } 165 | 166 | void GridMap::loadMap ( const std::string& img_dir, const int& init_x, const int& init_y, const double& cell_size ) 167 | { 168 | /* 利用opencv读取地图图片 */ 169 | cv::Mat cv_map = cv::imread(img_dir); 170 | cv::Mat cv_gray; 171 | cv::cvtColor(cv_map, cv_gray, cv::COLOR_RGB2GRAY); 172 | 173 | cv::flip(cv_gray, cv_gray, 1); 174 | 175 | size_x_ = cv_gray.cols; 176 | size_y_ = cv_gray.rows; 177 | init_x_ = init_x; 178 | init_y_ = init_y; 179 | cell_size_ = cell_size; 180 | 181 | bel_data_.resize ( size_x_, size_y_ ); 182 | bel_data_.setOnes() *= 0.5; //全部设为0.5的概率 183 | 184 | /* 为opencv图片显示相关 */ 185 | m_one_.resize(size_x_, size_y_); 186 | m_one_.setOnes(); 187 | m_show_.resize(size_x_, size_y_); 188 | m_show_.setOnes() * 0.5; 189 | 190 | for (size_t x=0; x(y, x); 195 | 196 | // TODO 这里的参数没有加入到配置文件中 197 | switch (pixel) 198 | { 199 | case 0: //占用 200 | bel_data_(x, y) = 1.0; 201 | break; 202 | 203 | case 254: //free 204 | bel_data_(x, y) = 0.0; 205 | break; 206 | 207 | case 205: //unknown 208 | bel_data_(x, y) = 0.5; 209 | break; 210 | } //switch 211 | }// for y 212 | }// for x 213 | 214 | 215 | }// load map 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | 224 | -------------------------------------------------------------------------------- /src/localizer.cc: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #include 5 | #include 6 | 7 | Localizer::Localizer ( Robot* robot, GridMap* map, MotionModel* motion_model, MeasurementModel* measurement_model , size_t nParticles ) : 8 | robot_ ( robot ), map_ ( map ), motion_model_ ( motion_model ), measurement_model_ ( measurement_model ),nParticles_ ( nParticles ) 9 | { 10 | is_init_ = false; 11 | 12 | /* 初始化粒子 */ 13 | const double minX = map->minX(); 14 | const double maxX = map->maxX(); 15 | const double minY = map->minY(); 16 | const double maxY = map->maxY(); 17 | cv::RNG rng ( cv::getTickCount() ); 18 | size_t N = 0; 19 | double weight = 1.0 / nParticles; 20 | while ( N < nParticles ) 21 | { 22 | double x = rng.uniform ( minX, maxX ); 23 | double y = rng.uniform ( minY, maxY ); 24 | double th = rng.uniform ( -PI, PI ); 25 | 26 | /* 判断是否在地图内 & 判断是否在可行区域内 */ 27 | double bel; 28 | if ( !map->getGridBel ( x, y, bel ) ) 29 | { 30 | continue; 31 | } 32 | if ( bel != 0.0 ) //0.0的区域是可行驶区域 33 | { 34 | continue; 35 | } 36 | 37 | /* 构造一个粒子 */ 38 | N++; 39 | Particle pt ( Pose2d ( x, y, th ), weight ); 40 | particles_.push_back ( pt ); 41 | } 42 | } 43 | 44 | void Localizer::motionUpdate ( const Pose2d& odom ) 45 | { 46 | const double MIN_DIST = 0.02; // TODO param 如果运动太近的话就不更新了，防止出现角度计算错误 47 | if ( !is_init_ ) //首次 48 | { 49 | last_odom_pose_ = odom; 50 | is_init_ = true; 51 | return; 52 | } 53 | 54 | /* 计算ut */ 55 | double dx = odom.x_ - last_odom_pose_.x_; 56 | double dy = odom.y_ - last_odom_pose_.y_; 57 | double delta_trans = sqrt ( dx * dx + dy * dy ); 58 | double delta_rot1 = atan2 ( dy, dx ) - last_odom_pose_.theta_; 59 | Pose2d::NormAngle ( delta_rot1 ); 60 | /* 处理纯旋转 */ 61 | if(delta_trans < 0.01) 62 | delta_rot1 = 0; 63 | double delta_rot2 = odom.theta_ - last_odom_pose_.theta_ - delta_rot1; 64 | Pose2d::NormAngle ( delta_rot2 ); 65 | 66 | for ( size_t i = 0; i < nParticles_; i ++ ) 67 | { 68 | motion_model_->sampleMotionModelOdometry ( delta_rot1, delta_trans, delta_rot2, particles_.at ( i ).pose_ ); // for each particle 69 | } 70 | 71 | last_odom_pose_ = odom; 72 | } 73 | 74 | 75 | void Localizer::measurementUpdate ( const sensor_msgs::LaserScanConstPtr& scan ) 76 | { 77 | if ( !is_init_ ) 78 | { 79 | return; 80 | } 81 | 82 | /* 获取激光的信息 */ 83 | const double& ang_min = scan->angle_min; 84 | const double& ang_max = scan->angle_max; 85 | const double& ang_inc = scan->angle_increment; 86 | const double& range_max = scan->range_max; 87 | const double& range_min = scan->range_min; 88 | 89 | for ( size_t np = 0; np < nParticles_; np ++ ) 90 | { 91 | Particle& pt = particles_.at ( np ); 92 | /* for every laser beam */ 93 | for ( size_t i = 0; i < scan->ranges.size(); i ++ ) 94 | { 95 | /* 获取当前beam的距离 */ 96 | const double& R = scan->ranges.at ( i ); 97 | if ( R > range_max || R < range_min ) 98 | continue; 99 | 100 | double angle = ang_inc * i + ang_min; 101 | double cangle = cos ( angle ); 102 | double sangle = sin ( angle ); 103 | Eigen::Vector2d p_l ( 104 | R * cangle, 105 | R* sangle 106 | ); //在激光雷达坐标系下的坐标 107 | 108 | /* 转换到世界坐标系下 */ 109 | Pose2d laser_pose = pt.pose_ * robot_->T_r_l_; 110 | Eigen::Vector2d p_w = laser_pose * p_l; 111 | 112 | /* 更新weight */ 113 | double likelihood = measurement_model_->getGridLikelihood ( p_w ( 0 ), p_w ( 1 ) ); 114 | 115 | /* 整合多个激光beam用的加法， 用乘法收敛的太快 */ 116 | pt.weight_ += likelihood; 117 | }// for every laser beam 118 | } // for every particle 119 | 120 | /* 权重归一化 */ 121 | normalization(); 122 | 123 | /* TODO 这里最好使用书上的Argument 的重采样 + KLD重采样方法. 124 | *重采样频率太高会导致粒子迅速退化*/ 125 | static int cnt = -1; 126 | if ( (cnt ++) % 10 == 0 ) //减少重采样的次数 127 | reSample(); //重采样 128 | } 129 | 130 | void Localizer::normalization() 131 | { 132 | if ( !is_init_ ) 133 | { 134 | return; 135 | } 136 | 137 | long double sum = 0; 138 | for ( size_t i = 0; i < nParticles_; i ++ ) 139 | { 140 | Particle& pt = particles_.at ( i ); 141 | 142 | /* 走出地图的粒子干掉 */ 143 | double bel = 0.0; 144 | if (!map_->getGridBel(pt.pose_.x_, pt.pose_.y_, bel) ) 145 | pt.weight_ = 0.0; 146 | // else if (bel != 0.0) //如果走到未知区域就给一个很低的权值 147 | // pt.weight_ = 1.0 / nParticles_; 148 | 149 | sum += pt.weight_; 150 | } 151 | long double eta = 1.0 / sum; 152 | for ( size_t i = 0; i < nParticles_; i ++ ) 153 | { 154 | Particle& pt = particles_.at ( i ); 155 | pt.weight_ *= eta; 156 | } 157 | } 158 | 159 | 160 | void Localizer::reSample() 161 | { 162 | if ( !is_init_ ) 163 | return; 164 | 165 | /* 重采样 */ 166 | std::vector new_particles; 167 | cv::RNG rng ( cv::getTickCount() ); 168 | long double inc = 1.0 / nParticles_; 169 | long double r = rng.uniform ( 0.0, inc ); 170 | long double c = particles_.at ( 0 ).weight_; 171 | int i = 0; 172 | 173 | for ( size_t m = 0; m < nParticles_; m ++ ) 174 | { 175 | long double U = r + m * inc; 176 | while ( U > c ) 177 | { 178 | i = i+1; 179 | c = c + particles_.at ( i ).weight_; 180 | } 181 | particles_.at ( i ).weight_ = inc; 182 | 183 | /* 新采样的粒子加了高斯，稍微增加一下多样性 */ 184 | Particle new_pt = particles_.at(i); 185 | new_pt.pose_.x_ += rng.gaussian(0.02); 186 | new_pt.pose_.y_ += rng.gaussian(0.02); 187 | new_pt.pose_.theta_ += rng.gaussian(0.02); 188 | Pose2d::NormAngle(new_pt.pose_.theta_); 189 | new_particles.push_back ( new_pt ); 190 | } 191 | particles_ = new_particles; 192 | } 193 | 194 | void Localizer::particles2RosPoseArray ( geometry_msgs::PoseArray& pose_array ) 195 | { 196 | pose_array.header.frame_id = "odom"; 197 | pose_array.header.stamp = ros::Time::now(); 198 | for ( size_t i = 0; i < particles_.size(); i ++ ) 199 | { 200 | Particle& pt = particles_.at ( i ); 201 | geometry_msgs::Pose pose; 202 | pose.position.x = pt.pose_.x_; 203 | pose.position.y = pt.pose_.y_; 204 | pose.position.z = 0; 205 | pose.orientation = tf::createQuaternionMsgFromYaw ( pt.pose_.theta_ ); 206 | pose_array.poses.push_back ( pose ); 207 | } 208 | } 209 | 210 | // kate: indent-mode cstyle; indent-width 4; replace-tabs on; 211 | -------------------------------------------------------------------------------- /src/measurement_model.cc: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #include 5 | #define PI 3.1415926 6 | 7 | MeasurementModel::MeasurementModel ( GridMap* map, const double& sigma, const double& rand ): 8 | map_(map), sigma_(sigma), rand_(rand) 9 | { 10 | /* 初始化似然域模型, 预先计算的似然域模型的格子大小比占有栅格小1倍 */ 11 | size_x_ = 2 * map->size_x_; 12 | size_y_ = 2 * map->size_y_; 13 | init_x_ = 2 * map->init_x_; 14 | init_y_ = 2 * map->init_y_; 15 | cell_size_ = 0.5 * map->cell_size_; 16 | 17 | likelihood_data_.resize(size_x_ , size_y_); 18 | likelihood_data_.setZero(); 19 | 20 | /* 构造障碍物的KD-Tree */ 21 | pcl::PointCloud::Ptr cloud (new pcl::PointCloud); 22 | 23 | for(int i = 0; i < map->size_x_; i ++) 24 | for(int j = 0; j < map->size_y_; j ++) 25 | { 26 | if(map->bel_data_(i, j) == 1.0) //是障碍物就加到KD数中 27 | { 28 | pcl::PointXY pt; 29 | pt.x = (i - map->init_x_) * map->cell_size_; 30 | pt.y = (j - map->init_y_) * map->cell_size_; 31 | cloud->push_back(pt); 32 | } 33 | } 34 | kd_tree_.setInputCloud(cloud); 35 | 36 | /* 对每个格子计算likelihood */ 37 | for(double i = 0; i < size_x_; i += 0.9) 38 | for(double j = 0; j < size_y_; j +=0.9) 39 | { 40 | /* 计算double x, y */ 41 | double x = ( i - init_x_)* cell_size_; 42 | double y = ( j- init_y_ ) * cell_size_; 43 | double likelihood = likelihoodFieldRangFinderModel(x, y); 44 | setGridLikelihood(x, y, likelihood); 45 | } 46 | } 47 | 48 | 49 | double MeasurementModel::likelihoodFieldRangFinderModel ( const double& x, const double& y ) 50 | { 51 | /* 找到最近的距离 */ 52 | pcl::PointXY search_point; 53 | search_point.x = x; 54 | search_point.y = y; 55 | std::vector k_indices; 56 | std::vector k_sqr_distances; 57 | int nFound = kd_tree_.nearestKSearch(search_point, 1, k_indices, k_sqr_distances); 58 | double dist = k_sqr_distances.at(0); 59 | 60 | /* 高斯 + random */ 61 | return gaussion(0.0, sigma_, dist) + rand_; 62 | } 63 | 64 | double MeasurementModel::gaussion ( const double& mu, const double& sigma, double x) 65 | { 66 | return (1.0 / (sqrt( 2 * PI ) * sigma) ) * exp( -0.5 * (x-mu) * (x-mu) / (sigma* sigma) ); 67 | } 68 | 69 | bool MeasurementModel::getIdx ( const double& x, const double& y, Eigen::Vector2i& idx ) 70 | { 71 | int xidx = cvFloor( x / cell_size_ ) + init_x_; 72 | int yidx = cvFloor( y /cell_size_ )+ init_y_; 73 | 74 | if((xidx < 0) || (yidx < 0) || (xidx >= size_x_) || (yidx >= size_y_)) 75 | return false; 76 | idx << xidx , yidx; 77 | return true; 78 | } 79 | 80 | double MeasurementModel::getGridLikelihood ( const double& x, const double& y) 81 | { 82 | Eigen::Vector2i idx; 83 | if(!getIdx(x, y, idx)) 84 | return rand_; 85 | return likelihood_data_(idx(0), idx(1)); 86 | } 87 | 88 | bool MeasurementModel::setGridLikelihood ( const double& x, const double& y, const double& likelihood ) 89 | { 90 | Eigen::Vector2i idx; 91 | if(!getIdx(x, y, idx)) 92 | return false; 93 | likelihood_data_(idx(0), idx(1)) = likelihood; 94 | return true; 95 | } 96 | 97 | 98 | cv::Mat MeasurementModel::toCvMat() 99 | { 100 | /* 构造出opencv格式显示 */ 101 | cv::Mat map(cv::Size(size_x_, size_y_), CV_64FC1, likelihood_data_.data(), cv::Mat::AUTO_STEP); 102 | /* 翻转 */ 103 | cv::flip(map, map, 0); 104 | return map; 105 | } 106 | -------------------------------------------------------------------------------- /src/motion_model.cc: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #include 5 | 6 | MotionModel::MotionModel ( const double& alpha1, const double& alpha2, const double& alpha3, const double& alpha4 ): 7 | alpha1_(alpha1), alpha2_(alpha2), alpha3_(alpha3), alpha4_(alpha4) 8 | { 9 | rng_ = cv::RNG(cv::getTickCount()); 10 | } 11 | 12 | void MotionModel::sampleMotionModelOdometry ( const double& delta_rot1, const double& delta_trans, const double& delta_rot2, Pose2d& xt ) 13 | { 14 | /* 处理后退的问题 */ 15 | double delta_rot1_PI = delta_rot1 - PI; 16 | double delta_rot2_PI = delta_rot2 - PI; 17 | Pose2d::NormAngle(delta_rot1_PI); 18 | Pose2d::NormAngle(delta_rot2_PI); 19 | double delta_rot1_noise = std::min(fabs(delta_rot1), fabs( delta_rot1_PI) ); 20 | double delta_rot2_noise = std::min(fabs(delta_rot2), fabs( delta_rot2_PI) ); 21 | 22 | double delta_rot1_2 = delta_rot1_noise*delta_rot1_noise; 23 | double delta_rot2_2 = delta_rot2_noise * delta_rot2_noise; 24 | double delta_trans_2 = delta_trans * delta_trans; 25 | 26 | /* 采样 */ 27 | double delta_rot1_hat = delta_rot1 - rng_.gaussian(alpha1_ * delta_rot1_2 + alpha2_ * delta_trans_2); 28 | double delta_trans_hat = delta_trans - rng_.gaussian(alpha3_ * delta_trans_2 + alpha4_ * delta_rot1_2 + alpha4_ * delta_rot2_2); 29 | double delta_rot2_hat = delta_rot2 - rng_.gaussian(alpha1_ * delta_rot2_2 + alpha2_ * delta_trans_2); 30 | 31 | xt.x_ += delta_trans_hat * cos( xt.theta_ + delta_rot1_hat ); 32 | xt.y_ += delta_trans_hat * sin( xt.theta_ + delta_rot1_hat ); 33 | xt.theta_ += (delta_rot1_hat + delta_rot2_hat); 34 | xt.NormAngle(xt.theta_); 35 | } 36 | -------------------------------------------------------------------------------- /test/odometry.cc: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #include 5 | #include 6 | #include 7 | #include 8 | #include 9 | #include 10 | 11 | // global variable 12 | #define PI 3.1415926 13 | ros::Publisher g_odom_pub; 14 | boost::shared_ptr odom_broadcaster; 15 | double g_kl, g_kr, g_b; 16 | 17 | void odometryCallback(const geometry_msgs::QuaternionStamped::ConstPtr& encoder); 18 | 19 | int main(int argc, char **argv) { 20 | // init ros 21 | ros::init(argc, argv, "odometry"); 22 | ros::NodeHandle nh; 23 | 24 | /*TODO default parameters*/ 25 | nh.getParam("/odometry/robot/kl", g_kl); 26 | nh.getParam("/odometry/robot/kr", g_kr); 27 | nh.getParam("/odometry/robot/b", g_b); 28 | 29 | odom_broadcaster.reset(new tf::TransformBroadcaster()); 30 | ros::Subscriber sub = nh.subscribe("/mbot/encoder", 1000, odometryCallback); 31 | g_odom_pub = nh.advertise("mbot/odometry", 1000); 32 | 33 | ros::spin(); 34 | return 1; 35 | } 36 | 37 | void odometryCallback(const geometry_msgs::QuaternionStamped::ConstPtr& encoder) 38 | { 39 | // TODO 参数需要更在标定后做更精细的修正 40 | const double KL = g_kl; //m/tick 41 | const double KR = g_kr; //m/tick 42 | const double B = g_b; //width 43 | 44 | static double pre_time = 0.0; 45 | static double x = 0.0, y =0.0, theta = 0.0; // pose of robot 46 | static double pre_en_l1 = 0, pre_en_l2 = 0, pre_en_r1 = 0, pre_en_r2 = 0; 47 | 48 | // 读取四个编码器的值，四个编码器的值是存储在一个四元数里的 49 | double en_l1 = encoder->quaternion.x; 50 | double en_l2 = encoder->quaternion.y; 51 | double en_r1 = encoder->quaternion.z; 52 | double en_r2 = encoder->quaternion.w; 53 | 54 | //读取时间戳 55 | double cur_time = encoder->header.stamp.toSec(); 56 | double delta_t = 0.0; //以秒为单位 57 | if(pre_time == 0.0)//处理第一帧数据 58 | { 59 | pre_time = cur_time; 60 | pre_en_l1 = en_l1; 61 | pre_en_l2 = en_l2; 62 | pre_en_r1 = en_r1; 63 | pre_en_r2 = en_r2; 64 | } 65 | else 66 | { 67 | // read deltas 68 | delta_t = cur_time - pre_time; 69 | pre_time = cur_time; 70 | double delta_en_l1 = en_l1 - pre_en_l1; 71 | double delta_en_l2 = en_l2 - pre_en_l2; 72 | double delta_en_r1 = en_r1 - pre_en_r1; 73 | double delta_en_r2 = en_r2 - pre_en_r2; 74 | double delta_en_l = (delta_en_l1 + delta_en_l2)* 0.5; 75 | double delta_en_r = (delta_en_r1 + delta_en_r2)* 0.5; 76 | 77 | pre_en_l1 = en_l1; 78 | pre_en_l2 = en_l2; 79 | pre_en_r1 = en_r1; 80 | pre_en_r2 = en_r2; 81 | 82 | //cal odometry 83 | double delta_theta = (KR*delta_en_r - KL*delta_en_l) / B; 84 | double delta_s = 0.5 *(KR*delta_en_r + KL*delta_en_l); 85 | double delta_x = delta_s * cos(theta + 0.5*delta_theta); 86 | double delta_y = delta_s * sin(theta + 0.5*delta_theta); 87 | 88 | x = x + delta_x; 89 | y = y + delta_y; 90 | theta = theta + delta_theta; 91 | // 修正角度 92 | if(theta > PI) 93 | theta -= 2 * PI; 94 | else if(theta < -PI) 95 | theta += 2 * PI; 96 | 97 | double vx = delta_x / delta_t; 98 | double vy = delta_y / delta_t; 99 | double omega = delta_theta / delta_t; 100 | 101 | //since all odometry is 6DOF we'll need a quaternion created from yaw 102 | geometry_msgs::Quaternion odom_quat = tf::createQuaternionMsgFromYaw(theta); 103 | 104 | //first, we'll publish the transform over tf 105 | geometry_msgs::TransformStamped odom_trans; 106 | odom_trans.header.stamp = ros::Time::now(); 107 | odom_trans.header.frame_id = "odom"; 108 | odom_trans.child_frame_id = "base_link"; 109 | 110 | odom_trans.transform.translation.x = x; 111 | odom_trans.transform.translation.y = y; 112 | odom_trans.transform.translation.z = 0.0; 113 | odom_trans.transform.rotation = odom_quat; 114 | 115 | //send the transform 116 | odom_broadcaster->sendTransform(odom_trans); 117 | 118 | //publish odometry 119 | nav_msgs::Odometry odom; 120 | odom.header.stamp = ros::Time::now(); 121 | odom.header.frame_id = "odom"; 122 | odom.child_frame_id = "base_link"; 123 | 124 | odom.pose.pose.position.x = x; 125 | odom.pose.pose.position.y = y; 126 | odom.pose.pose.orientation = odom_quat; 127 | 128 | odom.twist.twist.angular.z = omega; 129 | odom.twist.twist.linear.x = vx; 130 | odom.twist.twist.linear.y = vy; 131 | 132 | g_odom_pub.publish(odom); 133 | }// 134 | }// -------------------------------------------------------------------------------- /test/pf_localization_node.cc: -------------------------------------------------------------------------------- 1 | // Copyright (C) 2018 Dongsheng Yang 2 | //(Biologically Inspired Mobile Robot Laboratory, Robotics Institute, Beihang University) 3 | 4 | #include 5 | #include 6 | #include 7 | #include 8 | #include 9 | 10 | #include 11 | 12 | /* Global */ 13 | GridMap* g_map; 14 | ros::Subscriber g_odom_suber; 15 | ros::Publisher g_map_puber, g_particles_puber; 16 | Localizer* g_localizer; 17 | 18 | void odometryCallback ( const nav_msgs::OdometryConstPtr& odom ); 19 | void laserCallback ( const sensor_msgs::LaserScanConstPtr& scan ); 20 | 21 | int main ( int argc, char **argv ) 22 | { 23 | /***** 初始化ROS *****/ 24 | ros::init ( argc, argv, "PF_Localization" ); 25 | ros::NodeHandle nh; 26 | 27 | /* 加载地图 */ 28 | std::string map_img_dir, map_cfg_dir; 29 | int initx, inity; 30 | double cell_size; 31 | /* TODO 错误处理 */ 32 | nh.getParam ( "/pf_localization_node/map_dir", map_img_dir ); 33 | nh.getParam ( "/pf_localization_node/map/initx", initx ); 34 | nh.getParam ( "/pf_localization_node/map/inity", inity ); 35 | nh.getParam ( "/pf_localization_node/map/cell_size", cell_size ); 36 | GridMap* map = new GridMap(); 37 | map->loadMap ( map_img_dir, initx, inity, cell_size ); 38 | g_map = map; 39 | 40 | /* 初始化机器人 */ 41 | Pose2d T_r_l; 42 | double x, y, theta; 43 | /* TODO 错误处理 */ 44 | nh.getParam ( "/pf_localization_node/robot_laser/x", x ); 45 | nh.getParam ( "/pf_localization_node/robot_laser/y", y ); 46 | nh.getParam ( "/pf_localization_node/robot_laser/theta", theta ); 47 | T_r_l = Pose2d ( x, y, theta ); 48 | Robot* robot = new Robot ( 0.0, 0.0, 0.0, T_r_l ); 49 | 50 | /* 初始化运动模型 */ 51 | double a1, a2, a3, a4; 52 | nh.getParam ( "/pf_localization_node/motion_model/alpha1", a1 ); 53 | nh.getParam ( "/pf_localization_node/motion_model/alpha2", a2 ); 54 | nh.getParam ( "/pf_localization_node/motion_model/alpha3", a3 ); 55 | nh.getParam ( "/pf_localization_node/motion_model/alpha4", a4 ); 56 | MotionModel* motion_model = new MotionModel ( a1, a2, a3, a4 ); 57 | 58 | /* 初始化观测模型 */ 59 | double sigma, rand; 60 | nh.getParam ( "/pf_localization_node/measurement_model/sigma", sigma ); 61 | nh.getParam ( "/pf_localization_node/measurement_model/rand", rand ); 62 | std::cout << "\n\n正在计算似然域模型, 请稍后......\n\n"; 63 | MeasurementModel* measurement_model = new MeasurementModel ( map, sigma, rand ); 64 | std::cout << "\n\n似然域模型计算完毕. 开始接收数据.\n\n"; 65 | 66 | /* 初始化定位器 */ 67 | int n_particles; 68 | nh.getParam ( "/pf_localization_node/particle_filter/n_particles", n_particles ); 69 | g_localizer = new Localizer ( robot, map, motion_model, measurement_model, n_particles ); 70 | 71 | /* 初始Topic */ 72 | g_odom_suber = nh.subscribe ( "/mbot/odometry", 1, odometryCallback ); 73 | ros::Subscriber laser_suber = nh.subscribe ( "/scan", 1, laserCallback ); 74 | g_map_puber = nh.advertise ( "pf_localization/grid_map", 1 ); 75 | g_particles_puber = nh.advertise ( "pf_localization/particles", 1 ); 76 | ros::spin(); 77 | } 78 | 79 | void odometryCallback ( const nav_msgs::OdometryConstPtr& odom ) 80 | { 81 | /* 获取机器人姿态 */ 82 | double x = odom->pose.pose.position.x; 83 | double y = odom->pose.pose.position.y; 84 | double theta = tf::getYaw ( odom->pose.pose.orientation ); 85 | Pose2d rpose ( x, y, theta ); 86 | 87 | /* 运动更新 */ 88 | g_localizer->motionUpdate ( rpose ); 89 | 90 | /* 发布粒子 */ 91 | geometry_msgs::PoseArray pose_array; 92 | g_localizer->particles2RosPoseArray ( pose_array ); 93 | g_particles_puber.publish ( pose_array ); 94 | 95 | } 96 | 97 | void laserCallback ( const sensor_msgs::LaserScanConstPtr& scan ) 98 | { 99 | /* 测量更新 */ 100 | g_localizer->measurementUpdate ( scan ); 101 | 102 | /* 低频发布地图 */ 103 | static int cnt = -1; 104 | if ( (cnt ++) % 100 == 0 ) 105 | { 106 | nav_msgs::OccupancyGrid occ_map; 107 | g_map->toRosOccGridMap ( "odom", occ_map ); 108 | g_map_puber.publish ( occ_map ); 109 | } 110 | } 111 | 112 | // kate: indent-mode cstyle; indent-width 4; replace-tabs on; 113 | --------------------------------------------------------------------------------