├── CMakeLists.txt ├── LICENSE ├── README.md ├── assets ├── PSO_Planner.png ├── pso_demo1.gif ├── pso_demo2.gif ├── pso_fitness.png └── pso_ros_1.gif ├── include ├── global_planner_ros.h ├── pso.h └── trajectoryGeneration.h ├── package.xml ├── params └── pso_planner.yaml ├── pso_planner_plugin.xml └── src ├── global_planner_ros.cpp ├── pso.cpp ├── pso_plan_node.cpp └── trajectoryGeneration.cpp /CMakeLists.txt: -------------------------------------------------------------------------------- 1 | cmake_minimum_required(VERSION 3.0.2) 2 | project(pso_global_planner) 3 | 4 | add_compile_options(-std=c++11) 5 | 6 | find_package(catkin REQUIRED 7 | angles 8 | COMPONENTS 9 | costmap_2d 10 | geometry_msgs 11 | nav_msgs 12 | pluginlib 13 | tf2_geometry_msgs 14 | tf2_ros 15 | nav_core 16 | roscpp 17 | std_msgs 18 | visualization_msgs 19 | tf 20 | ) 21 | 22 | catkin_package( 23 | INCLUDE_DIRS include 24 | LIBRARIES ${PROJECT_NAME} 25 | CATKIN_DEPENDS 26 | costmap_2d 27 | geometry_msgs 28 | nav_msgs 29 | pluginlib 30 | tf2_geometry_msgs 31 | tf2_ros 32 | nav_core 33 | roscpp 34 | std_msgs 35 | visualization_msgs 36 | tf 37 | ) 38 | 39 | include_directories( 40 | include 41 | ${catkin_INCLUDE_DIRS} 42 | ) 43 | 44 | add_library(${PROJECT_NAME} 45 | src/global_planner_ros.cpp 46 | src/trajectoryGeneration.cpp 47 | src/pso.cpp 48 | ) 49 | 50 | add_dependencies(${PROJECT_NAME} ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS}) 51 | target_link_libraries(${PROJECT_NAME} ${catkin_LIBRARIES}) 52 | 53 | add_executable(pso_planner src/pso_plan_node.cpp) 54 | add_dependencies(pso_planner ${${PROJECT_NAME}_EXPORTED_TARGETS} ${catkin_EXPORTED_TARGETS}) 55 | target_link_libraries(pso_planner ${PROJECT_NAME} ${catkin_LIBRARIES}) 56 | 57 | install(TARGETS ${PROJECT_NAME} 58 | ARCHIVE DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION} 59 | LIBRARY DESTINATION ${CATKIN_PACKAGE_LIB_DESTINATION} 60 | RUNTIME DESTINATION ${CATKIN_GLOBAL_BIN_DESTINATION}) 61 | 62 | install(DIRECTORY include/${PROJECT_NAME}/ 63 | DESTINATION ${CATKIN_PACKAGE_INCLUDE_DESTINATION} 64 | PATTERN ".svn" EXCLUDE) 65 | 66 | install(FILES pso_planner_plugin.xml 67 | DESTINATION ${CATKIN_PACKAGE_SHARE_DESTINATION}) 68 | 69 | 70 | -------------------------------------------------------------------------------- /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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It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. 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 | # PSO Global Path Planner for ROS 2 | 3 | ![PSO_Planner](assets/PSO_Planner.png) 4 | 5 |

6 | ubuntu 8 | ROS 9 |

10 | 11 | ## 1. Introduction 12 | 13 | This ROS Global Planner Plugin implements the PSO (Particle Swarm Optimization) path planning algorithm. The examples below demonstrate its usage in both static and dynamic environments: 14 | 15 | ### (1) Static Environment: 16 | 17 |
18 | demo1.gif 19 |
20 | 21 | ### (2) Dynamic Environment: 22 | 23 |
24 | demo2.gif 25 |
26 | 27 | ## 2. How to Use 28 | 29 | ### (1) Method One: Utilized as a ROS Global Planner Plugin. 30 | 31 | You can employ this plugin within the ROS navigation package by configuring the global path planner plugin to `pso_planner/globalMotionPlannerROS` in the launch file where the 'move_base' node is situated. Additionally, load the parameter configuration file `pso_planner.yaml`. An example is provided below: 32 | 33 | ```bash 34 | 35 | 36 | 37 | ... 38 | ... 39 | ... 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 48 | ... 49 | ... 50 | ... 51 | 52 | 53 | ``` 54 | 55 | ### (2) Method Two: Employing through the ros_motion_planning library. 56 | 57 | In addition to the method described above, which involves using it as an independent ROS global path planner plugin, we also offer an alternative approach. We have integrated the PSO global path planner into the ROS-based motion planning library, [ros_motion_planning](https://github.com/ai-winter/ros_motion_planning). You can easily utilize it by setting the 'robot1_global_planner' parameter in the ['user_config.yaml'](https://github.com/ai-winter/ros_motion_planning/blob/master/src/user_config/user_config.yaml) file of this motion planning library to 'pso'. An example is provided below: 58 | 59 | ```bash 60 | map: "warehouse" 61 | world: "warehouse" 62 | rviz_file: "sim_env.rviz" 63 | 64 | robots_config: 65 | - robot1_type: "turtlebot3_waffle" 66 | robot1_global_planner: "pso" 67 | robot1_local_planner: "dwa" 68 | 69 | 70 | ... 71 | ... 72 | ... 73 | 74 | plugins: 75 | 76 | 77 | ... 78 | ... 79 | ... 80 | 81 | ``` 82 | 83 | The demonstration of the results is as follows: 84 | 85 |
86 | demo3.gif 87 | pso_fitness.png 88 |
-------------------------------------------------------------------------------- /assets/PSO_Planner.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JZX-MY/pso_global_planner/f1e8286c9908721af4ba52cdd889084b53550867/assets/PSO_Planner.png -------------------------------------------------------------------------------- /assets/pso_demo1.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JZX-MY/pso_global_planner/f1e8286c9908721af4ba52cdd889084b53550867/assets/pso_demo1.gif -------------------------------------------------------------------------------- /assets/pso_demo2.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JZX-MY/pso_global_planner/f1e8286c9908721af4ba52cdd889084b53550867/assets/pso_demo2.gif -------------------------------------------------------------------------------- /assets/pso_fitness.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JZX-MY/pso_global_planner/f1e8286c9908721af4ba52cdd889084b53550867/assets/pso_fitness.png -------------------------------------------------------------------------------- /assets/pso_ros_1.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/JZX-MY/pso_global_planner/f1e8286c9908721af4ba52cdd889084b53550867/assets/pso_ros_1.gif -------------------------------------------------------------------------------- /include/global_planner_ros.h: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: global_planner_ros.cpp 4 | * @breif: ROS related framework for global path planner 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-13 7 | * @version: 1.0 8 | * 9 | * Copyright (c) 2023,Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | 15 | #ifndef GLOBAL_PLANNER_ROS_H 16 | #define GLOBAL_PLANNER_ROS_H 17 | 18 | #include 19 | #include 20 | #include 21 | #include 22 | #include 23 | #include 24 | #include 25 | #include 26 | #include 27 | 28 | #include "pso.h" 29 | 30 | 31 | namespace global_motion_planner 32 | { 33 | 34 | class globalMotionPlannerROS : public nav_core::BaseGlobalPlanner 35 | { 36 | 37 | public: 38 | /** 39 | * @brief Default constructor of the plugin 40 | */ 41 | globalMotionPlannerROS(); 42 | 43 | globalMotionPlannerROS(std::string name, costmap_2d::Costmap2DROS* costmap_ros); 44 | 45 | ~globalMotionPlannerROS(); 46 | 47 | /** 48 | * @brief Initialization function for the PlannerCore object 49 | * @param name The name of this planner 50 | * @param costmap_ros A pointer to the ROS wrapper of the costmap to use for planning 51 | */ 52 | void initialize(std::string name, costmap_2d::Costmap2DROS* costmap_ros); 53 | 54 | /** 55 | * @brief Given a goal pose in the world, compute a plan 56 | * @param start The start pose 57 | * @param goal The goal pose 58 | * @param plan The plan... filled by the planner 59 | * @return True if a valid plan was found, false otherwise 60 | */ 61 | bool makePlan(const geometry_msgs::PoseStamped& start, 62 | const geometry_msgs::PoseStamped& goal, 63 | std::vector& plan); 64 | 65 | /** 66 | * @brief Generates a plan from a given path. 67 | * @param path Vector of pairs representing the path in (x, y) coordinates. 68 | * @param plan Vector of PoseStamped messages representing the generated plan. 69 | * @return bool True if the plan is successfully generated, false otherwise. 70 | */ 71 | bool getPlanFromPath(std::vector< std::pair >& path, std::vector& plan); 72 | 73 | 74 | /** 75 | * @brief Compute the euclidean distance (straight-line distance) between two points 76 | * @param px1 point 1 x 77 | * @param py1 point 1 y 78 | * @param px2 point 2 x 79 | * @param py2 point 2 y 80 | * @return the distance computed 81 | */ 82 | double distance(double px1, double py1, double px2, double py2); 83 | 84 | /** 85 | * @brief Check if there is a collision. 86 | * @param x coordinate (cartesian system) 87 | * @param y coordinate (cartesian system) 88 | * @return True is the point collides and false otherwise 89 | */ 90 | bool collision(double x, double y); //是否为障碍物 91 | 92 | /** 93 | * @brief Checks if the specified world coordinates are in the vicinity of a free space. 94 | * @param wx The world x-coordinate to be checked. 95 | * @param wy The world y-coordinate to be checked. 96 | * @return bool True if the specified coordinates are around a free space, false otherwise. 97 | */ 98 | bool isAroundFree(double wx, double wy); 99 | 100 | /** 101 | * @brief Checks for collision between two points in a circular region. 102 | * @param x1 The x-coordinate of the first point. 103 | * @param y1 The y-coordinate of the first point. 104 | * @param x2 The x-coordinate of the second point. 105 | * @param y2 The y-coordinate of the second point. 106 | * @param radius The radius of the circular region for collision checking. 107 | * @return bool True if there is a collision, false otherwise. 108 | */ 109 | bool pointCircleCollision(double x1, double y1, double x2, double y2, double radius); 110 | 111 | /** 112 | * @brief Optimizes the orientation of poses in a given plan. 113 | * @param plan Vector of PoseStamped messages representing the plan to be optimized. 114 | */ 115 | void optimizationOrientation(std::vector &plan); 116 | 117 | /** 118 | * @brief Checks if the line segment between two points is free from obstacles. 119 | * @param p1 Pair representing the coordinates (x, y) of the first point. 120 | * @param p2 Pair representing the coordinates (x, y) of the second point. 121 | * @return bool True if the line segment is free from obstacles, false otherwise. 122 | */ 123 | bool isLineFree(const std::pair p1,const std::pair p2); 124 | 125 | protected: 126 | 127 | costmap_2d::Costmap2D* costmap_; // costmap 128 | costmap_2d::Costmap2DROS* costmap_ros_; // costmap ros 129 | global_motion_planner::PSO* g_planner_; // planner 130 | unsigned int nx_, ny_; // costmap size 131 | double origin_x_, origin_y_; // costmap origin 132 | double resolution_; // costmap resolution 133 | std::string frame_id_; 134 | ros::Publisher plan_pub_; 135 | 136 | private: 137 | 138 | bool initialized_; 139 | 140 | }; 141 | } // global_motion_planner namespace 142 | #endif 143 | -------------------------------------------------------------------------------- /include/pso.h: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: pso.h 4 | * @breif: Contains the Particle Swarm Optimization(PSO) planner class 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-12 7 | * @version: 1.1 8 | * 9 | * Copyright (c) 2023,Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | 15 | #ifndef PSO_H 16 | #define PSO_H 17 | 18 | #include 19 | #include 20 | #include 21 | #include 22 | #include "trajectoryGeneration.h" 23 | #include 24 | #include 25 | 26 | using PositionSequence = std::vector>>; 27 | 28 | namespace global_motion_planner 29 | { 30 | struct Particle 31 | { 32 | std::vector> position; // Particle position 33 | std::vector> velocity; // Particle velocity 34 | double fitness; // Particle fitness 35 | std::vector> personal_best_pos; // Personal best position in iteration 36 | double personal_best_fitness; // Personal best fitness in iteration 37 | 38 | Particle() = default; 39 | 40 | Particle(const std::vector>& initial_position, 41 | const std::vector>& initial_velocity, 42 | double initial_fitness) 43 | : position(initial_position), 44 | velocity(initial_velocity), 45 | fitness(initial_fitness), 46 | personal_best_pos(initial_position), 47 | personal_best_fitness(initial_fitness) 48 | { 49 | } 50 | }; 51 | 52 | /** 53 | * @brief Class for objects that plan using the PSO algorithm 54 | */ 55 | 56 | class PSO 57 | { 58 | public: 59 | /** 60 | * @brief Construct a new PSO object 61 | * @param nx pixel number in costmap x direction 62 | * @param ny pixel number in costmap y direction 63 | * @param resolution costmap resolution 64 | * @param origin_x origin coordinate in the x direction. 65 | * @param origin_y origin coordinate in the y direction. 66 | * @param n_particles number of particles 67 | * @param n_inherited number of inherited particles 68 | * @param pointNum number of position points contained in each particle 69 | * @param w_inertial inertia weight 70 | * @param w_social social weight 71 | * @param w_cognitive cognitive weight 72 | * @param obs_factor obstacle factor(greater means obstacles) 73 | * @param max_speed The maximum movement speed of particles 74 | * @param initposmode Set the generation mode for the initial position points of the particle swarm 75 | * @param pub_particles Boolean flag to publish particles. 76 | * @param max_iter maximum iterations 77 | */ 78 | PSO(int nx, int ny, double resolution, double origin_x, double origin_y, int n_particles,int n_inherited, int pointNum , double w_inertial, double w_social, double w_cognitive, double obs_factor,int max_speed,int initposmode ,bool pub_particles,int max_iter); 79 | ~PSO(); 80 | 81 | /** 82 | * @brief PSO implementation 83 | * @param global_costmap global costmap 84 | * @param start start node 85 | * @param goal goal node 86 | * @param path optimal path consists of Node 87 | * @return true if path found, else false 88 | */ 89 | bool plan(const unsigned char* global_costmap, const std::pair& start, const std::pair& goal, std::vector< std::pair>& path); 90 | 91 | /** 92 | * @brief Generate n particles with pointNum_ positions each within the map range 93 | * @param initialPositions The initial position sequence of particle swarm 94 | * @param start_d starting point 95 | * @param goal_d Target point 96 | */ 97 | void generateRandomInitialPositions(PositionSequence &initialPositions,const std::pair start_d,const std::pair goal_d); 98 | 99 | /** 100 | * @brief Generate an initial position point sequence within a circular area, located within the map range 101 | * @param initialPositions The initial position sequence of particle swarm 102 | * @param start_d starting point 103 | * @param goal_d Target point 104 | */ 105 | void generateCircularInitialPositions(PositionSequence &initialPositions,const std::pair start_d,const std::pair goal_d); 106 | 107 | /** 108 | * @brief Calculate Obstacle avoidance cost 109 | * @param global_costmap global costmap 110 | * @param pso_path Path to perform collision detection 111 | * @return The collision cost of the path 112 | */ 113 | double ObstacleCost(const unsigned char* global_costmap,const std::vector>& pso_path); 114 | 115 | /** 116 | * @brief A function to update the particle velocity 117 | * @param particle Particles to be updated for velocity 118 | * @param global_best Global optimal particle 119 | * @param gen randomizer 120 | */ 121 | void updateParticleVelocity(Particle& particle,const Particle& global_best,std::mt19937& gen); 122 | 123 | /** 124 | * @brief A function to update the particle position 125 | * @param particle Particles to be updated for velocity 126 | */ 127 | void updateParticlePosition(Particle& particle); 128 | 129 | 130 | /** 131 | * @brief Particle update optimization iteration 132 | * @param particle Particles to be updated for velocity 133 | * @param best_particle Global optimal particle 134 | * @param start_d starting point 135 | * @param goal_d Target point 136 | * @param index_i Particle ID 137 | * @param global_costmap global costmap 138 | * @param gen randomizer 139 | */ 140 | void optimizeParticle(Particle& particle, Particle& best_particle, const unsigned char* global_costmap, 141 | const std::pair& start_d, const std::pair& goal_d, 142 | const int& index_i,std::mt19937& gen) ; 143 | 144 | /** 145 | * @brief Clamps a value within a specified range. 146 | * @tparam T The type of the values to be clamped. 147 | * @param value The value to be clamped. 148 | * @param low The lower bound of the range. 149 | * @param high The upper bound of the range. 150 | * @return const T& The clamped value within the specified range. 151 | */ 152 | template 153 | const T& clamp(const T& value, const T& low, const T& high) {return std::max(low, std::min(value, high));} 154 | 155 | /** 156 | * @brief Custom comparison function for ascending order. 157 | * @param a The first element to be compared. 158 | * @param b The second element to be compared. 159 | * @return bool True if 'a' is less than 'b', indicating ascending order; otherwise, false. 160 | */ 161 | static bool ascendingOrder(int a, int b) { return a < b;} 162 | 163 | /** 164 | * @brief Custom comparison function for descending order. 165 | * @param a The first element to be compared. 166 | * @param b The second element to be compared. 167 | * @return bool True if 'a' is greater than 'b', indicating descending order; otherwise, false. 168 | */ 169 | static bool descendingOrder(int a, int b){ return a > b;} 170 | 171 | 172 | /** 173 | * @brief Publishes particle markers based on given positions and index. 174 | * @param positions Vector of pairs representing positions (x, y) of particles. 175 | * @param index Index identifier for the particles. 176 | */ 177 | void publishParticleMarkers(const std::vector>& positions, const int& index); 178 | 179 | /** 180 | * @brief Transform from grid map(x, y) to grid index(i) 181 | * @param x grid map x 182 | * @param y grid map y 183 | * @return index 184 | */ 185 | int grid2Index (int x, int y); 186 | 187 | 188 | protected: 189 | int nx_,ny_,ns_; // the number of grids on the x-axis and y-axis of the map, as well as the total number of grids 190 | double resolution_; // map resolution 191 | double origin_x_,origin_y_; // origin coordinate in the x、y direction. 192 | bool pub_particles_; // boolean flag to publish particles. 193 | int max_iter_; // maximum iterations 194 | int n_particles_; // number of particles 195 | int n_inherited_; // number of inherited particles 196 | int pointNum_; // number of position points contained in each particle 197 | double w_inertial_, w_social_, w_cognitive_; // Weight coefficients for fitness calculation: inertia weight, social weight, cognitive weight 198 | double obs_factor_; // obstacle factor(greater means obstacles) 199 | int max_speed_; // The maximum velocity of particle motion 200 | int initposmode_; // Set the generation mode for the initial position points of the particle swarm 201 | 202 | 203 | private: 204 | unsigned char lethal_cost_=253; //lethal cost 205 | ros::Publisher particle_pub; //The publisher of real-time particle visualization 206 | int GlobalBest_particle_; //The ID of the globally optimal particle 207 | std::mutex particles_lock_; //thread lock 208 | std::vector inherited_particles_; //inherited particles 209 | trajectoryGeneration path_generation; //Path generation 210 | }; 211 | 212 | } // namespace global_planner 213 | #endif 214 | -------------------------------------------------------------------------------- /include/trajectoryGeneration.h: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: trajectoryGeneration.h 4 | * @breif: Contains trajectory generation class 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-4 7 | * @version: 1.0 8 | * 9 | * Copyright (c) 2023,Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | 15 | #ifndef TRAJECTORY_GENERATION_H 16 | #define TRAJECTORY_GENERATION_H 17 | 18 | #include 19 | #include 20 | 21 | class trajectoryGeneration 22 | { 23 | public: 24 | trajectoryGeneration(); 25 | ~trajectoryGeneration(); 26 | 27 | static int splineOrder; //Set the order of the B-spline curve 28 | 29 | /** 30 | * @brief Using quasi uniform B-spline curves for trajectory generation 31 | * @param plan Key points&generated trajectories 32 | * @param k Order of B-spline curve 33 | */ 34 | void B_spline_curve(std::vector> &plan, int k); 35 | 36 | 37 | /** 38 | * @brief Generate B-spline curve control points 39 | * @param start_d starting point 40 | * @param goal_d Target point 41 | * @param initial_position Intermediate control point 42 | * @param initial_point B-spline control points 43 | */ 44 | void GenerateControlPoints(const std::pair& start_d, const std::pair& goal_d, 45 | const std::vector>& initial_position, 46 | std::vector>& initial_point); 47 | 48 | /** 49 | * @brief Calculate the distance between two points 50 | * @param point1 First point 51 | * @param point2 Second point 52 | * @return the distance between two points 53 | */ 54 | double calculateDistance(const std::pair& point1, const std::pair& point2); 55 | 56 | /** 57 | * @brief Calculate path length 58 | * @param path The path to be calculated 59 | * @return path length 60 | */ 61 | double calculatePathLength(const std::vector>& path); 62 | 63 | 64 | private: 65 | double BaseFun(int i, int k, double u, std::vector NodeVector); 66 | }; 67 | 68 | #endif // TRAJECTORY_GENERATION_H 69 | -------------------------------------------------------------------------------- /package.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | pso_global_planner 4 | 0.0.0 5 | The pso_global_planner package 6 | 7 | JZX-MY 8 | 9 | GPLv3 10 | 11 | catkin 12 | 13 | pluginlib 14 | roscpp 15 | std_msgs 16 | nav_core 17 | geometry_msgs 18 | costmap_2d 19 | nav_msgs 20 | tf2_geometry_msgs 21 | tf2_ros 22 | visualization_msgs 23 | tf 24 | angles 25 | 26 | pluginlib 27 | roscpp 28 | costmap_2d 29 | geometry_msgs 30 | nav_msgs 31 | tf2_geometry_msgs 32 | nav_core 33 | std_msgs 34 | visualization_msgs 35 | tf 36 | angles 37 | 38 | pluginlib 39 | roscpp 40 | std_msgs 41 | nav_core 42 | costmap_2d 43 | geometry_msgs 44 | nav_msgs 45 | tf2_geometry_msgs 46 | tf2_ros 47 | visualization_msgs 48 | tf 49 | angles 50 | 51 | 52 | 53 | 54 | 55 | 56 | -------------------------------------------------------------------------------- /params/pso_planner.yaml: -------------------------------------------------------------------------------- 1 | globalMotionPlannerROS: 2 | 3 | ## Particle Swarm Optimization(PSO) planner 4 | # number of particles 5 | n_particles: 50 6 | # number of inherited particles (Note: Need to be less than parameter n_ Particles) 7 | n_inherited: 20 8 | # number of position points contained in each particle 9 | pointNum: 5 10 | # The maximum velocity of particle motion 11 | max_speed: 40 12 | # inertia weight 13 | w_inertial: 1.0 14 | # social weight 15 | w_social: 2.0 16 | # cognitive weight 17 | w_cognitive: 1.2 18 | # obstacle factor(greater means obstacles) 19 | obs_factor: 0.39 20 | # Set the generation mode for the initial position points of the particle swarm 21 | # 1: Randomly generate initial positions of particle swarm within the map range 22 | # 2: Randomly generate initial particle swarm positions within the circular area of the starting and target points 23 | initposmode: 2 24 | # Whether to publish particles 25 | pub_particles: false 26 | # maximum iterations 27 | pso_max_iter: 5 28 | 29 | -------------------------------------------------------------------------------- /pso_planner_plugin.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | This is PSO Global Planner Plugin by Jing Zongxin. 4 | 5 | 6 | -------------------------------------------------------------------------------- /src/global_planner_ros.cpp: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: global_planner_ros.cpp 4 | * @breif: ROS related framework for global path planner 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-13 7 | * @version: 1.0 8 | * 9 | * Copyright (c) 2023,Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | 15 | #include 16 | #include 17 | #include 18 | 19 | #include "global_planner_ros.h" 20 | 21 | PLUGINLIB_EXPORT_CLASS(global_motion_planner::globalMotionPlannerROS, nav_core::BaseGlobalPlanner) 22 | 23 | namespace global_motion_planner 24 | { 25 | 26 | globalMotionPlannerROS::globalMotionPlannerROS() : costmap_(nullptr), initialized_(false){} 27 | 28 | globalMotionPlannerROS::globalMotionPlannerROS(std::string name, costmap_2d::Costmap2DROS* costmap_ros) :costmap_ros_(costmap_ros),initialized_(false) 29 | { 30 | initialize(name, costmap_ros); 31 | } 32 | 33 | globalMotionPlannerROS::~globalMotionPlannerROS() 34 | { 35 | if (g_planner_) 36 | { 37 | delete g_planner_; 38 | g_planner_ = NULL; 39 | } 40 | } 41 | 42 | // Variable initialization 43 | void globalMotionPlannerROS::initialize(std::string name, costmap_2d::Costmap2DROS* costmap_ros) 44 | { 45 | if (!initialized_) 46 | { 47 | // Initialize map 48 | costmap_ros_ = costmap_ros; 49 | costmap_ = costmap_ros->getCostmap(); 50 | frame_id_ = costmap_ros->getGlobalFrameID(); 51 | // get costmap properties 52 | nx_ = costmap_->getSizeInCellsX(), ny_ = costmap_->getSizeInCellsY(); 53 | origin_x_ = costmap_->getOriginX(), origin_y_ = costmap_->getOriginY(); 54 | resolution_ = costmap_->getResolution(); 55 | 56 | ros::NodeHandle private_nh("~/" + name); 57 | plan_pub_ = private_nh.advertise("plan",1); //发布全局计算 58 | 59 | bool pub_particles; 60 | int n_particles,n_inherited,pointNum,max_speed,initposmode,pso_max_iter; 61 | double obs_factor, w_inertial, w_social, w_cognitive; 62 | private_nh.param("n_particles", n_particles, 50); // number of particles 63 | private_nh.param("n_inherited", n_inherited, 20); // number of inherited particles 64 | private_nh.param("pointNum", pointNum, 5); // number of position points contained in each particle 65 | private_nh.param("obs_factor", obs_factor, 0.39); // obstacle factor(greater means obstacles) 66 | private_nh.param("max_speed", max_speed,40); // The maximum velocity of particle motion 67 | private_nh.param("w_inertial", w_inertial,1.0); // inertia weight 68 | private_nh.param("w_social", w_social, 2.0); // social weight 69 | private_nh.param("w_cognitive", w_cognitive, 1.2); // cognitive weight 70 | private_nh.param("initposmode", initposmode, 2); // Set the generation mode for the initial position points of the particle swarm 71 | private_nh.param("pub_particles", pub_particles, false); // Whether to publish particles 72 | private_nh.param("pso_max_iter", pso_max_iter, 5); // maximum iterations 73 | 74 | g_planner_ = new PSO(nx_, ny_, resolution_ ,origin_x_,origin_y_, n_particles,n_inherited, pointNum, w_inertial, w_social, w_cognitive, obs_factor, max_speed ,initposmode ,pub_particles,pso_max_iter); 75 | 76 | ROS_INFO("PSO planner initialized successfully"); 77 | initialized_ = true; 78 | } 79 | else 80 | { 81 | ROS_WARN("This planner has already been initialized... doing nothing"); 82 | } 83 | } 84 | 85 | // Path planning 86 | bool globalMotionPlannerROS::makePlan(const geometry_msgs::PoseStamped& start, 87 | const geometry_msgs::PoseStamped& goal, 88 | std::vector& plan) 89 | { 90 | if (!initialized_) 91 | { 92 | ROS_ERROR("This planner has not been initialized yet, but it is being used, please call initialize() before use"); 93 | return false; 94 | } 95 | 96 | std::pair start_node, goal_node; 97 | unsigned int mx = 0,my = 0; 98 | 99 | if(this->collision(start.pose.position.x, start.pose.position.y)) 100 | { 101 | ROS_WARN("failed to get a path.start point is obstacle."); 102 | return false; 103 | } 104 | else 105 | { 106 | this->costmap_->worldToMap(start.pose.position.x,start.pose.position.y,mx,my); 107 | start_node.first =static_cast(mx); 108 | start_node.second=static_cast(my); 109 | } 110 | 111 | if(this->collision(goal.pose.position.x, goal.pose.position.y)) 112 | { 113 | ROS_WARN("failed to get a path.goal point is obstacle."); 114 | return false; 115 | } 116 | else 117 | { 118 | this->costmap_->worldToMap(goal.pose.position.x,goal.pose.position.y,mx,my); 119 | goal_node.first =static_cast(mx); 120 | goal_node.second=static_cast(my); 121 | } 122 | 123 | std::vector< std::pair> path; 124 | plan.clear(); 125 | 126 | double start_time = ros::Time::now().toSec(); 127 | 128 | bool path_found = g_planner_->plan(costmap_->getCharMap(), start_node, goal_node, path); 129 | 130 | if (path_found) 131 | { 132 | if (getPlanFromPath(path, plan)) 133 | { 134 | geometry_msgs::PoseStamped goal_copy = goal; 135 | goal_copy.header.stamp = ros::Time::now(); 136 | plan.push_back(goal_copy); 137 | } 138 | else 139 | { 140 | ROS_ERROR("Failed to get a plan from path when a legal path was found. This shouldn't happen."); 141 | } 142 | } 143 | else 144 | { 145 | ROS_ERROR("Failed to get a path."); 146 | } 147 | 148 | // path point attitude correction 149 | optimizationOrientation(plan); 150 | 151 | // publish visulization plan 152 | nav_msgs::Path path_pose; 153 | path_pose.header.frame_id = this->frame_id_; 154 | path_pose.header.stamp = ros::Time::now(); 155 | path_pose.poses = plan; 156 | plan_pub_.publish(path_pose); 157 | 158 | return !plan.empty(); 159 | } 160 | 161 | bool globalMotionPlannerROS::getPlanFromPath(std::vector< std::pair >& path, std::vector& plan) 162 | { 163 | plan.clear(); 164 | unsigned int mx = 0,my = 0; 165 | double wx, wy; 166 | 167 | for (int i = 0; i < path.size(); i++) 168 | { 169 | mx=static_cast(path[i].first); 170 | my=static_cast(path[i].second); 171 | this->costmap_->mapToWorld(mx,my,wx,wy); 172 | // coding as message type 173 | geometry_msgs::PoseStamped pose; 174 | pose.header.stamp = ros::Time::now(); 175 | pose.header.frame_id = frame_id_; 176 | pose.pose.position.x = wx; 177 | pose.pose.position.y = wy; 178 | pose.pose.position.z = 0.0; 179 | pose.pose.orientation.x = 0.0; 180 | pose.pose.orientation.y = 0.0; 181 | pose.pose.orientation.z = 0.0; 182 | pose.pose.orientation.w = 1.0; 183 | plan.push_back(pose); 184 | } 185 | 186 | return !plan.empty(); 187 | } 188 | 189 | // Optimizes the orientation of poses in a given plan. 190 | void globalMotionPlannerROS::optimizationOrientation(std::vector &plan) 191 | { 192 | size_t num = plan.size()-1; 193 | if(num < 1) 194 | return; 195 | for(size_t i=0;i p1, const std::pair p2) 213 | { 214 | std::pair ptmp; 215 | ptmp.first = 0.0; 216 | ptmp.second = 0.0; 217 | 218 | double dist = sqrt( (p2.second-p1.second) * (p2.second-p1.second) + 219 | (p2.first-p1.first) * (p2.first-p1.first) ); 220 | if (dist < this->resolution_) 221 | { 222 | return true; 223 | } 224 | else 225 | { 226 | int value = int(floor(dist/this->resolution_)); 227 | double theta = atan2(p2.second - p1.second, 228 | p2.first - p1.first); 229 | int n = 1; 230 | for (int i = 0;i < value; i++) 231 | { 232 | ptmp.first = p1.first + this->resolution_*cos(theta) * n; 233 | ptmp.second = p1.second + this->resolution_*sin(theta) * n; 234 | if (collision(ptmp.first, ptmp.second)) 235 | return false; 236 | n++; 237 | } 238 | return true; 239 | } 240 | } 241 | 242 | // Calculate the distance between two points 243 | double globalMotionPlannerROS::distance(double px1, double py1, double px2, double py2) 244 | { 245 | return sqrt((px1 - px2)*(px1 - px2) + (py1 - py2)*(py1 - py2)); 246 | } 247 | 248 | // Check if the checkpoint is an obstacle 249 | bool globalMotionPlannerROS::collision(double x, double y) 250 | { 251 | unsigned int mx,my; 252 | if(!this->costmap_->worldToMap(x,y,mx,my)) 253 | return true; 254 | if ((mx >= costmap_->getSizeInCellsX()) || (my >= costmap_->getSizeInCellsY())) 255 | return true; 256 | if (costmap_->getCost(mx, my) >= costmap_2d::INSCRIBED_INFLATED_OBSTACLE) 257 | return true; 258 | return false; 259 | } 260 | 261 | // Check if there are any obstacles around the checkpoint 262 | bool globalMotionPlannerROS::isAroundFree(double wx, double wy) 263 | { 264 | unsigned int mx, my; 265 | if(!this->costmap_->worldToMap(wx,wy,mx,my)) 266 | return false; 267 | if(mx <= 1 || my <= 1 || mx >= this->costmap_->getSizeInCellsX()-1 || my >= this->costmap_->getSizeInCellsY()-1) 268 | return false; 269 | int x,y; 270 | for(int i=-1;i<=1;i++) 271 | { 272 | for(int j=-1;j<=1;j++) 273 | { 274 | x = static_cast(mx) + i; 275 | y = static_cast(my) + j; 276 | if(this->costmap_->getCost(static_cast(x),static_cast(y)) >= costmap_2d::INSCRIBED_INFLATED_OBSTACLE) 277 | return false; 278 | } 279 | } 280 | return true; 281 | } 282 | 283 | 284 | }; // global_motion_planner 285 | -------------------------------------------------------------------------------- /src/pso.cpp: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: pso.cpp 4 | * @breif: Contains the Particle Swarm Optimization(PSO) planner class 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-12 7 | * @version: 1.1 8 | * 9 | * Copyright (c) 2023, Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | #include 15 | #include 16 | #include 17 | #include 18 | #include 19 | #include "pso.h" 20 | 21 | 22 | namespace global_motion_planner 23 | { 24 | /** 25 | * @brief Construct a new PSO object 26 | * @param nx pixel number in costmap x direction 27 | * @param ny pixel number in costmap y direction 28 | * @param resolution costmap resolution 29 | * @param origin_x origin coordinate in the x direction. 30 | * @param origin_y origin coordinate in the y direction. 31 | * @param n_particles number of particles 32 | * @param n_inherited number of inherited particles 33 | * @param pointNum number of position points contained in each particle 34 | * @param w_inertial inertia weight 35 | * @param w_social social weight 36 | * @param w_cognitive cognitive weight 37 | * @param obs_factor obstacle factor(greater means obstacles) 38 | * @param max_speed The maximum movement speed of particles 39 | * @param initposmode Set the generation mode for the initial position points of the particle swarm 40 | * @param pub_particles Boolean flag to publish particles. 41 | * @param max_iter maximum iterations 42 | */ 43 | PSO::PSO(int nx, int ny, double resolution, double origin_x, double origin_y,int n_particles,int n_inherited,int pointNum , double w_inertial, double w_social, double w_cognitive, double obs_factor ,int max_speed, int initposmode, bool pub_particles,int max_iter) 44 | : nx_(nx) 45 | , ny_(ny) 46 | , ns_(nx*ny) 47 | , resolution_(resolution) 48 | , origin_x_(origin_x) 49 | , origin_y_(origin_y) 50 | , n_particles_(n_particles) 51 | , n_inherited_(n_inherited) 52 | , pointNum_(pointNum) 53 | , w_inertial_(w_inertial) 54 | , w_social_(w_social) 55 | , w_cognitive_(w_cognitive) 56 | , obs_factor_(obs_factor) 57 | , max_speed_(max_speed) 58 | , initposmode_(initposmode) 59 | , pub_particles_(pub_particles) 60 | , max_iter_(max_iter) 61 | { 62 | inherited_particles_.emplace_back(std::vector>(pointNum, std::make_pair(1, 1)), 63 | std::vector>(pointNum, std::make_pair(0, 0)), 64 | 0.0); 65 | // Initialize ROS publisher 66 | ros::NodeHandle nh; 67 | particle_pub = nh.advertise("particle_swarm_markers", 10); 68 | } 69 | 70 | PSO::~PSO() 71 | { 72 | } 73 | 74 | /** 75 | * @brief PSO implementation 76 | * @param global_costmap global costmap 77 | * @param start start node 78 | * @param goal goal node 79 | * @param path optimal path consists of Node 80 | * @return true if path found, else false 81 | */ 82 | bool PSO::plan(const unsigned char* global_costmap, const std::pair& start, const std::pair& goal, std::vector< std::pair>& path) 83 | { 84 | 85 | std::cout<<" PSO planning started..."< particles; 94 | std::vector> initial_point; 95 | std::pair start_d(static_cast(start.first), static_cast(start.second)); 96 | std::pair goal_d(static_cast(goal.first), static_cast(goal.second)); 97 | 98 | //Generate initial position of particle swarm 99 | if(initposmode_==1){generateRandomInitialPositions(initialPositions,start_d,goal_d);} 100 | else{generateCircularInitialPositions(initialPositions,start_d,goal_d);} 101 | 102 | std::cout<<"PSO: Successfully generated initial position of particle swarm"<> initial_position; 108 | 109 | if ((i> initial_velocity(pointNum_, std::make_pair(0, 0)); 119 | //Generate B-spline curve control points 120 | path_generation.GenerateControlPoints(start_d,goal_d,initial_position,initial_point); 121 | //Generate B-spline curves 122 | path_generation.B_spline_curve(initial_point, path_generation.splineOrder); 123 | //Calculate path length 124 | pathLength = path_generation.calculatePathLength(initial_point); 125 | //collision detection 126 | obstacle_cost=ObstacleCost(global_costmap,initial_point); 127 | //Calculate particle fitness 128 | initial_fitness = 100000.0 / (pathLength + 1000*obstacle_cost); 129 | 130 | if ((i==0)||(initial_fitness>Best_particle.fitness)) 131 | { 132 | GlobalBest_particle_=i; 133 | Best_particle.fitness=initial_fitness; 134 | } 135 | //Create and add particle objects to containers 136 | particles.emplace_back(initial_position, initial_velocity, initial_fitness); 137 | 138 | } 139 | 140 | Best_particle.position=particles[GlobalBest_particle_].position; 141 | 142 | std::cout<<"PSO: Successfully generated initial particle swarm"< particle_list = std::vector(n_particles_); 156 | for (size_t i = 0; i < n_particles_; ++i) 157 | particle_list[i] = std::thread(&PSO::optimizeParticle, this, std::ref(particles[i]), std::ref(Best_particle), std::cref(global_costmap), std::cref(start_d), std::cref(goal_d), i, std::ref(gen)); 158 | for (size_t i = 0; i < n_particles_; ++i) 159 | particle_list[i].join(); 160 | 161 | Best_particle.position=particles[GlobalBest_particle_].personal_best_pos; 162 | } 163 | 164 | //Generating Paths from Optimal Particles 165 | path_generation.GenerateControlPoints(start_d,goal_d,Best_particle.position,initial_point); 166 | path_generation.B_spline_curve(initial_point, path_generation.splineOrder); 167 | 168 | std::cout<<"PSO: Iteration completed, optimal fitness is: "<(initial_point[0].first), static_cast(initial_point[0].second)); 177 | 178 | for (int p = 1; p (initial_point[p].first); 181 | int y = static_cast(initial_point[p].second); 182 | // Check if the current point is different from the last point 183 | if (x != path.back().first || y != path.back().second) 184 | { 185 | path.emplace_back(x, y); 186 | } 187 | } 188 | } 189 | 190 | //Update inheritance particles based on optimal fitness 191 | std::sort(particles.begin(), particles.end(), [](const Particle& a, const Particle& b) { return a.personal_best_fitness > b.personal_best_fitness;}); 192 | inherited_particles_.clear(); 193 | 194 | for (size_t inherit = 0; inherit < n_inherited_; ++inherit) 195 | { 196 | inherited_particles_.emplace_back(particles[inherit]); 197 | } 198 | 199 | if(!path.empty()){std::cout<<"PSO: Planning Successful ! "< start_d,const std::pair goal_d) 210 | { 211 | // Use a random device and engine to generate random numbers 212 | std::random_device rd; 213 | std::mt19937 gen(rd()); 214 | int x[pointNum_], y[pointNum_]; 215 | int point_id; 216 | 217 | //Calculate sequence direction 218 | bool xorder = (goal_d.first > start_d.first); 219 | bool yorder = (goal_d.second > start_d.second); 220 | 221 | for (int i = 0; i < n_particles_; ++i) 222 | { 223 | std::unordered_set visited; 224 | std::vector> particlePositions; 225 | point_id=0; 226 | // Generate pointNum_ unique coordinates 227 | while (point_id < pointNum_) 228 | { 229 | x[point_id] = std::uniform_int_distribution(0, nx_-1)(gen); 230 | y[point_id] = std::uniform_int_distribution(0, ny_-1)(gen); 231 | int uniqueId = x[point_id] * (ny_ + 1) + y[point_id]; // Represent coordinates by a unique ID 232 | 233 | // Check if the coordinates have already been used 234 | if (visited.find(uniqueId) == visited.end()) 235 | { 236 | point_id=point_id+1; 237 | visited.insert(uniqueId); 238 | } 239 | } 240 | 241 | //sort 242 | if(xorder){std::sort(x, x + pointNum_, &PSO::ascendingOrder);} 243 | else{std::sort(x, x + pointNum_, &PSO::descendingOrder);} 244 | 245 | if(yorder){std::sort(y, y + pointNum_, &PSO::ascendingOrder);} 246 | else{std::sort(y, y + pointNum_, &PSO::descendingOrder);} 247 | 248 | // Store elements from x and y in particlePositions 249 | for (int ii = 0; ii < pointNum_; ++ii) 250 | { 251 | particlePositions.emplace_back(x[ii], y[ii]); 252 | } 253 | 254 | initialPositions.push_back(particlePositions); 255 | } 256 | } 257 | 258 | // Generate n particles with pointNum_ positions each within the map range 259 | void PSO::generateCircularInitialPositions(PositionSequence &initialPositions,const std::pair start_d,const std::pair goal_d) 260 | { 261 | // Use a random device and engine to generate random numbers 262 | std::random_device rd; 263 | std::mt19937 gen(rd()); 264 | int x[pointNum_], y[pointNum_]; 265 | int point_id; 266 | //Calculate sequence direction 267 | bool xorder = (goal_d.first > start_d.first); 268 | bool yorder = (goal_d.second > start_d.second); 269 | // Calculate the center of the circle (midpoint between start and goal) 270 | int centerX = (start_d.first + goal_d.first) / 2; 271 | int centerY = (start_d.second + goal_d.second) / 2; 272 | // Calculate the radius of the circle (half of the distance between start and goal) 273 | double radius = path_generation.calculateDistance(start_d,goal_d) / 2.0; 274 | 275 | if (radius<5){radius=5;} 276 | 277 | for (int i = 0; i < n_particles_; ++i) 278 | { 279 | std::unordered_set visited; 280 | std::vector> particlePositions; 281 | point_id=0; 282 | // Generate pointNum_ unique coordinates 283 | while (point_id < pointNum_) 284 | { 285 | // Generate random angle in radians 286 | double angle = std::uniform_real_distribution(0, 2 * M_PI)(gen); 287 | // Generate random distance from the center within the circle 288 | double r = std::sqrt(std::uniform_real_distribution(0, 1)(gen)) * radius; 289 | // Convert polar coordinates to Cartesian coordinates 290 | x[point_id] = static_cast(std::round(centerX + r * std::cos(angle))); 291 | y[point_id] = static_cast(std::round(centerY + r * std::sin(angle))); 292 | 293 | // Check if the coordinates are within the map range 294 | if (x[point_id] >= 0 && x[point_id] < nx_ && y[point_id] >= 0 && y[point_id] < ny_) 295 | { 296 | int uniqueId = x[point_id] * (ny_ + 1) + y[point_id]; 297 | // Check if the coordinates have already been used 298 | if (visited.find(uniqueId) == visited.end()) 299 | { 300 | point_id = point_id + 1; 301 | visited.insert(uniqueId); 302 | } 303 | } 304 | 305 | } 306 | 307 | //sort 308 | if(xorder){std::sort(x, x + pointNum_, &PSO::ascendingOrder);} 309 | else{std::sort(x, x + pointNum_, &PSO::descendingOrder);} 310 | 311 | if(yorder){std::sort(y, y + pointNum_, &PSO::ascendingOrder);} 312 | else{std::sort(y, y + pointNum_, &PSO::descendingOrder);} 313 | 314 | // 将 x 和 y 中的元素存放到 particlePositions 中 315 | for (int ii = 0; ii < pointNum_; ++ii) 316 | { 317 | particlePositions.emplace_back(x[ii], y[ii]); 318 | } 319 | 320 | initialPositions.push_back(particlePositions); 321 | } 322 | } 323 | 324 | //Calculate Obstacle avoidance cost 325 | double PSO::ObstacleCost(const unsigned char* global_costmap,const std::vector>& pso_path) 326 | { 327 | int point_index; 328 | double Obscost=1; 329 | 330 | for (size_t i = 1; i < pso_path.size(); ++i) 331 | { 332 | point_index=grid2Index(static_cast(pso_path[i].first), static_cast(pso_path[i].second)); 333 | // next node hit the boundary or obstacle 334 | if ((point_index < 0) || (point_index >= ns_) || (global_costmap[point_index] >= lethal_cost_ * obs_factor_)) 335 | { 336 | Obscost=Obscost+1; 337 | } 338 | } 339 | 340 | return Obscost; 341 | 342 | } 343 | 344 | // A function to update the particle velocity 345 | void PSO::updateParticleVelocity(Particle& particle,const Particle& global_best,std::mt19937& gen) 346 | { 347 | //The random numbers are distributed between [0, 1). 348 | std::uniform_real_distribution dist(0.0, 1.0); 349 | 350 | // update Velocity 351 | for (size_t i = 0; i < pointNum_; ++i) 352 | { 353 | double rand1 = dist(gen); 354 | double rand2 = dist(gen); 355 | 356 | particle.velocity[i].first = static_cast( w_inertial_ * particle.velocity[i].first + 357 | w_social_ * rand1 * (particle.personal_best_pos[i].first - particle.position[i].first) + 358 | w_cognitive_ * rand2 * (global_best.position[i].first - particle.position[i].first)); 359 | 360 | particle.velocity[i].second = static_cast(w_inertial_ * particle.velocity[i].second + 361 | w_social_ * rand1 * (particle.personal_best_pos[i].second - particle.position[i].second) + 362 | w_cognitive_ * rand2 * (global_best.position[i].second - particle.position[i].second)); 363 | 364 | // Velocity limit 365 | particle.velocity[i].first =clamp(particle.velocity[i].first , -1*max_speed_, max_speed_); 366 | particle.velocity[i].second=clamp(particle.velocity[i].second, -1*max_speed_, max_speed_); 367 | } 368 | } 369 | 370 | // A function to update the particle position 371 | void PSO::updateParticlePosition(Particle& particle) 372 | { 373 | // update Position 374 | for (size_t i = 0; i < pointNum_; ++i) 375 | { 376 | particle.position[i].first = particle.position[i].first + particle.velocity[i].first; 377 | particle.position[i].second = particle.position[i].second+ particle.velocity[i].second; 378 | 379 | // Position limit 380 | particle.position[i].first =clamp(particle.position[i].first , 1, nx_-1); 381 | particle.position[i].second=clamp(particle.position[i].second, 1, ny_-1); 382 | } 383 | } 384 | 385 | // Particle update optimization iteration 386 | void PSO::optimizeParticle(Particle& particle, Particle& best_particle, const unsigned char* global_costmap, const std::pair& start_d, const std::pair& goal_d,const int& index_i,std::mt19937& gen) 387 | { 388 | 389 | std::vector> process_path; 390 | 391 | //update speed 392 | updateParticleVelocity(particle,best_particle,gen); 393 | //update position 394 | updateParticlePosition(particle); 395 | 396 | //Generate B-spline curve control points 397 | path_generation.GenerateControlPoints(start_d,goal_d,particle.position,process_path); 398 | //Generate B-spline curves 399 | path_generation.B_spline_curve(process_path, path_generation.splineOrder); 400 | //Calculate path length 401 | double pathLength = path_generation.calculatePathLength(process_path); 402 | //collision detection 403 | double obstacle_cost=ObstacleCost(global_costmap,process_path); 404 | //Calculate particle fitness 405 | particle.fitness = 100000.0 / (pathLength + 1000*obstacle_cost); 406 | 407 | // Update individual optima 408 | if (particle.fitness>particle.personal_best_fitness) 409 | { 410 | particle.personal_best_fitness=particle.fitness; 411 | particle.personal_best_pos=particle.position; 412 | } 413 | 414 | // Publish particle markers 415 | if(pub_particles_){publishParticleMarkers(particle.position, index_i);} 416 | 417 | //Update global optimal particles 418 | particles_lock_.lock(); 419 | 420 | if (particle.personal_best_fitness>best_particle.fitness) 421 | { 422 | best_particle.fitness=particle.personal_best_fitness; 423 | GlobalBest_particle_=index_i; 424 | } 425 | 426 | particles_lock_.unlock(); 427 | 428 | } 429 | 430 | 431 | void PSO::publishParticleMarkers(const std::vector>& positions, const int& index) 432 | { 433 | visualization_msgs::Marker marker; 434 | marker.header.frame_id = "map"; 435 | marker.header.stamp = ros::Time::now(); 436 | marker.ns = "particle_swarm"; 437 | marker.id = index; 438 | marker.type = visualization_msgs::Marker::POINTS; 439 | marker.action = visualization_msgs::Marker::ADD; 440 | marker.pose.orientation.w = 1.0; 441 | marker.scale.x = 0.1; 442 | marker.scale.y = 0.1; 443 | marker.color.r = 1.0; 444 | marker.color.a = 1.0; 445 | 446 | // Convert particle positions to geometry_msgs::Point 447 | for (const auto& position : positions) { 448 | geometry_msgs::Point p; 449 | p.x = origin_x_ + position.first * resolution_; 450 | p.y = origin_y_ + position.second * resolution_; 451 | p.z = 0.0; 452 | marker.points.push_back(p); 453 | } 454 | 455 | // Set the lifetime of the marker (e.g., 1 second) 456 | marker.lifetime = ros::Duration(1.0); 457 | 458 | particle_pub.publish(marker); 459 | } 460 | 461 | 462 | 463 | } // namespace global_planner -------------------------------------------------------------------------------- /src/pso_plan_node.cpp: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: pso_plan_node.cpp 4 | * @breif: PSO Global Path Planner ROS Node 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-13 7 | * @version: 1.0 8 | * 9 | * Copyright (c) 2023,Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | 15 | 16 | #include 17 | #include 18 | #include 19 | #include 20 | #include 21 | #include 22 | 23 | namespace global_motion_planner 24 | { 25 | 26 | class globalMotionPlannerWithCostmap : public globalMotionPlannerROS 27 | { 28 | public: 29 | globalMotionPlannerWithCostmap(std::string name, costmap_2d::Costmap2DROS* cmap); 30 | ~globalMotionPlannerWithCostmap(); 31 | 32 | private: 33 | void poseCallback(const geometry_msgs::PoseStamped::ConstPtr& goal); 34 | costmap_2d::Costmap2DROS* cmap_; 35 | ros::Subscriber pose_sub_; 36 | }; 37 | 38 | 39 | void globalMotionPlannerWithCostmap::poseCallback(const geometry_msgs::PoseStamped::ConstPtr& goal) 40 | { 41 | geometry_msgs::PoseStamped robot_pose; 42 | cmap_->getRobotPose(robot_pose); 43 | std::vector path; 44 | unsigned int mx = 0,my = 0; 45 | if(!this->costmap_->worldToMap(goal->pose.position.x,goal->pose.position.y,mx,my)) 46 | { 47 | std::cout << "worldToMap error" << std::endl; 48 | return; 49 | } 50 | if(this->costmap_->getCost(mx,my) != costmap_2d::FREE_SPACE) 51 | { 52 | std::cout << "The target point is unreachable." << std::endl; 53 | return; 54 | } 55 | makePlan(robot_pose, *goal, path); 56 | } 57 | 58 | globalMotionPlannerWithCostmap::globalMotionPlannerWithCostmap(std::string name, costmap_2d::Costmap2DROS* cmap) : 59 | globalMotionPlannerROS(name, cmap) 60 | { 61 | ros::NodeHandle private_nh("move_base_simple"); 62 | cmap_ = cmap; 63 | pose_sub_ = private_nh.subscribe("goal", 1, &globalMotionPlannerWithCostmap::poseCallback, this); 64 | } 65 | 66 | globalMotionPlannerWithCostmap::~globalMotionPlannerWithCostmap() 67 | {} 68 | 69 | } // namespace 70 | 71 | int main(int argc, char** argv) 72 | { 73 | ros::init(argc, argv, "pso_planner"); 74 | tf2_ros::Buffer buffer(ros::Duration(10)); 75 | tf2_ros::TransformListener tf(buffer); 76 | costmap_2d::Costmap2DROS gcm("global_costmap", buffer); 77 | global_motion_planner::globalMotionPlannerWithCostmap pppp("globalMotionPlannerROS", &gcm); 78 | ros::spin(); 79 | return 0; 80 | } 81 | 82 | -------------------------------------------------------------------------------- /src/trajectoryGeneration.cpp: -------------------------------------------------------------------------------- 1 | /*********************************************************** 2 | * 3 | * @file: trajectoryGeneration.cpp 4 | * @breif: Contains trajectory generation class 5 | * @author: Jing Zongxin 6 | * @update: 2023-12-4 7 | * @version: 1.0 8 | * 9 | * Copyright (c) 2023,Jing Zongxin 10 | * All rights reserved. 11 | * -------------------------------------------------------- 12 | * 13 | **********************************************************/ 14 | 15 | #include 16 | #include 17 | #include "trajectoryGeneration.h" 18 | 19 | trajectoryGeneration::trajectoryGeneration() 20 | { 21 | } 22 | 23 | trajectoryGeneration::~trajectoryGeneration() 24 | { 25 | } 26 | 27 | int trajectoryGeneration::splineOrder = 3; //Set the order of the B-spline curve 28 | 29 | //Generate B-spline curve control points 30 | void trajectoryGeneration::GenerateControlPoints(const std::pair& start_d, 31 | const std::pair& goal_d, 32 | const std::vector>& initial_position, 33 | std::vector>& initial_point) 34 | { 35 | initial_point.clear(); // Clear the vector to start fresh 36 | initial_point.push_back(start_d); 37 | std::pair last_point = start_d; 38 | 39 | for (const auto& position : initial_position) 40 | { 41 | double x = static_cast(position.first); 42 | double y = static_cast(position.second); 43 | // Check if the current point is different from the last point 44 | if (x != last_point.first || y != last_point.second) 45 | { 46 | initial_point.emplace_back(x, y); 47 | last_point = {x, y}; 48 | } 49 | } 50 | // Check if the goal point is different from the last point 51 | if (goal_d != last_point) 52 | { 53 | initial_point.push_back(goal_d); 54 | } 55 | } 56 | 57 | // Use De Boor-Cox recursion to calculate Bik(u) 58 | double trajectoryGeneration::BaseFun(int i, int k, double u, std::vector NodeVector) 59 | { 60 | // 1st order B-spline 61 | if (k == 0) 62 | { 63 | if ((u >= NodeVector[i]) && (u < NodeVector[i + 1])) 64 | { 65 | return 1.0; 66 | } 67 | else 68 | { 69 | return 0; 70 | } 71 | } 72 | // 2nd order and higher B-spline 73 | else 74 | { 75 | double Length1 = double(NodeVector[i + k]) - NodeVector[i]; 76 | double Length2 = double(NodeVector[i + k + 1]) - NodeVector[i + 1]; 77 | 78 | // Handle the case where the denominator is 0 by replacing it with 1, defining 0/0 as 0 79 | if (Length1 == 0) 80 | { 81 | Length1 = 1.0; 82 | } 83 | if (Length2 == 0) 84 | { 85 | Length2 = 1.0; 86 | } 87 | 88 | return ((double((u - NodeVector[i])) / Length1) * BaseFun(i, k - 1, u, NodeVector) + 89 | (double((NodeVector[i + k + 1] - u)) / Length2) * BaseFun(i + 1, k - 1, u, NodeVector)); 90 | } 91 | } 92 | 93 | // B-spline curve for trajectory smoothing, where K is the order 94 | void trajectoryGeneration::B_spline_curve(std::vector> &plan, int k) 95 | { 96 | // Rough estimate of the path length 97 | double plan_length = 0; 98 | 99 | for (int i = 1; i < plan.size(); i++) 100 | { 101 | plan_length = plan_length + std::sqrt((plan[i].first - plan[i - 1].first) * (plan[i].first - plan[i - 1].first) + 102 | (plan[i].second - plan[i - 1].second) * (plan[i].second - plan[i - 1].second)); 103 | } 104 | 105 | double d; 106 | std::pair new_control_point; 107 | // Extrapolate control points at the starting point 108 | d = std::sqrt((plan[1].first - plan[0].first) * (plan[1].first - plan[0].first) + 109 | (plan[1].second - plan[0].second) * (plan[1].second - plan[0].second)); 110 | new_control_point.first = plan[0].first - (0.1 / d) * (plan[1].first - plan[0].first); 111 | new_control_point.second = plan[0].second - (0.1 / d) * (plan[1].second - plan[0].second); 112 | plan.insert(plan.begin(), new_control_point); 113 | // Get the current number of control points 114 | int n = plan.size(); 115 | // Extrapolate control points at the end point 116 | d = std::sqrt((plan[n - 2].first - plan[n - 1].first) * (plan[n - 2].first - plan[n - 1].first) + 117 | (plan[n - 2].second - plan[n - 1].second) * (plan[n - 2].second - plan[n - 1].second)); 118 | new_control_point.first = plan[n - 1].first - (0.1 / d) * (plan[n - 2].first - plan[n - 1].first); 119 | new_control_point.second = plan[n - 1].second - (0.1 / d) * (plan[n - 2].second - plan[n - 1].second); 120 | plan.push_back(new_control_point); 121 | // Update the number of control points 122 | n = plan.size(); 123 | 124 | // Set up the node vector 125 | std::vector NodeVector; 126 | 127 | for (int i = 0; i < k + 1; i++) 128 | { 129 | NodeVector.push_back(0.0); 130 | } 131 | 132 | for (int i = 1; i <= (n - k - 1); i++) 133 | { 134 | NodeVector.push_back(double(i) / (n - k)); 135 | } 136 | 137 | for (int i = 0; i < k + 1; i++) 138 | { 139 | NodeVector.push_back(1.0); 140 | } 141 | 142 | // Set up u 143 | std::vector u; 144 | 145 | double temp_u = 0.0; 146 | double end_u = 1.0; 147 | 148 | // Calculate the interval of temp_u based on the rough estimate of the path length and 0.05m precision 149 | double temp_dt = 1 / plan_length; 150 | 151 | while (temp_u < end_u) 152 | { 153 | u.push_back(temp_u); 154 | temp_u = temp_u + temp_dt; 155 | } 156 | 157 | // Initialize Bik 158 | std::vector Bik; 159 | for (int i = 0; i < n; i++) 160 | { 161 | Bik.push_back(0); 162 | } 163 | 164 | // Initialize B-spline curve 165 | std::vector> B_plan; 166 | // Clever use of vector swap to release memory; the principle is to define a new empty container and then swap the contents of the two containers 167 | std::vector>().swap(B_plan); 168 | 169 | for (int i = 0; i < u.size(); i++) 170 | { 171 | double B_plan_x = 0; 172 | double B_plan_y = 0; 173 | std::pair temp_B_plan; 174 | 175 | for (int j = 0; j < n; j++) 176 | { 177 | Bik[j] = BaseFun(j, k - 1, u[i], NodeVector); 178 | } 179 | 180 | for (int m = 0; m < n; m++) 181 | { 182 | B_plan_x = B_plan_x + plan[m].first * Bik[m]; 183 | B_plan_y = B_plan_y + plan[m].second * Bik[m]; 184 | } 185 | temp_B_plan.first = B_plan_x; 186 | temp_B_plan.second = B_plan_y; 187 | B_plan.push_back(temp_B_plan); 188 | } 189 | 190 | // std::cout << B_plan.size()<& point1, const std::pair& point2) 198 | { 199 | double dx = point1.first - point2.first; 200 | double dy = point1.second - point2.second; 201 | return std::sqrt(dx * dx + dy * dy); 202 | } 203 | 204 | //Calculate path length 205 | double trajectoryGeneration::calculatePathLength(const std::vector>& path) 206 | { 207 | double length = 0.0; 208 | for (size_t i = 1; i < path.size(); ++i) 209 | { 210 | length += calculateDistance(path[i - 1], path[i]); 211 | } 212 | return length; 213 | } 214 | 215 | --------------------------------------------------------------------------------