{"id":13440324,"url":"https://github.com/ai-winter/matlab_motion_planning","last_synced_at":"2025-04-05T14:04:08.328Z","repository":{"id":73874041,"uuid":"598393958","full_name":"ai-winter/matlab_motion_planning","owner":"ai-winter","description":"Motion planning and Navigation of AGV/AMR：matlab implementation of Dijkstra, A*, Theta*, JPS, D*, LPA*, D* Lite, RRT, RRT*, RRT-Connect, Informed RRT*, ACO, Voronoi, PID, LQR, MPC, APF, RPP, DWA, DDPG, Bezier, B-spline, Dubins, Reeds-Shepp etc.","archived":false,"fork":false,"pushed_at":"2024-02-08T03:17:54.000Z","size":25740,"stargazers_count":423,"open_issues_count":2,"forks_count":66,"subscribers_count":10,"default_branch":"master","last_synced_at":"2025-03-29T13:05:23.496Z","etag":null,"topics":["a-star","ant-colony-optimization","artificial-potential-field","d-star","dijkstra","dynamic-window-approach","informed-rrt-star","jump-point-search","lqr-controller","motion-planning","mpc-control","pid-control","rrt","rrt-connect","rrt-star","theta-star","voronoi"],"latest_commit_sha":null,"homepage":"","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ai-winter.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-02-07T02:26:50.000Z","updated_at":"2025-03-27T03:16:46.000Z","dependencies_parsed_at":"2023-06-16T09:00:14.919Z","dependency_job_id":"9e8a442a-441f-4fb7-a97f-da1fd1a08a84","html_url":"https://github.com/ai-winter/matlab_motion_planning","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-winter%2Fmatlab_motion_planning","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-winter%2Fmatlab_motion_planning/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-winter%2Fmatlab_motion_planning/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ai-winter%2Fmatlab_motion_planning/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ai-winter","download_url":"https://codeload.github.com/ai-winter/matlab_motion_planning/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247345850,"owners_count":20924102,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["a-star","ant-colony-optimization","artificial-potential-field","d-star","dijkstra","dynamic-window-approach","informed-rrt-star","jump-point-search","lqr-controller","motion-planning","mpc-control","pid-control","rrt","rrt-connect","rrt-star","theta-star","voronoi"],"created_at":"2024-07-31T03:01:21.719Z","updated_at":"2025-04-05T14:04:08.308Z","avatar_url":"https://github.com/ai-winter.png","language":"MATLAB","funding_links":[],"categories":["MATLAB"],"sub_categories":[],"readme":"\n# Introduction\n\n`Motion planning` plans the state sequence of the robot without conflict between the start and goal. \n\n`Motion planning` mainly includes `Path planning` and `Trajectory planning`.\n\n* `Path Planning`: It's based on path constraints (such as obstacles), planning the optimal path sequence for the robot to travel without conflict between the start and goal.\n* `Trajectory planning`: It plans the motion state to approach the global path based on kinematics, dynamics constraints and path sequence.\n\nThis repository provides the implement of common `Motion planning` algorithm, welcome your star \u0026 fork \u0026 PR.\n\nThis repository provides the implementation of common Motion Planning algorithms. The theory analysis can be found at [motion-planning](https://blog.csdn.net/frigidwinter/category_11410243.html). Furthermore, we provide [ROS C++](https://github.com/ai-winter/ros_motion_planning) and [Python](https://github.com/ai-winter/matlab_motion_planning) version.\n\n\n# Quick Start\n\nThe file structure is shown below\n\n```\n├─gif\n├─examples\n│   ├─simulation_global.mlx\n│   ├─simulation_local.mlx\n│   ├─simulation_total.mlx\n├─global_planner\n│   ├─graph_search\n│   ├─sample_search\n│   └─evolutionary_search\n├─local_planner\n└─utils\n```\n\nThe global planning algorithm implementation is in the folder `global_planner` with `graph_search`, `sample_search` and `evolutionary search`; The local planning algorithm implementation is in the folder `local_planner`.\n\nTo start simulation, open `./simulation_global.mlx` or `./simulation_local.mlx` and select the algorithm, for example\n\n```matlab\nclear all;\nclc;\n\n% load environment\nload(\"gridmap_20x20_scene1.mat\");\nmap_size = size(grid_map);\nG = 1;\n\n% start and goal\nstart = [3, 2];\ngoal = [18, 29];\n\n% planner\nplanner_name = \"rrt\";\n\nplanner = str2func(planner_name);\n[path, flag, cost, expand] = planner(grid_map, start, goal);\n\n% visualization\nclf;\nhold on\n\n% plot grid map\nplot_grid(grid_map);\n% plot expand zone\nplot_expand(expand, map_size, G, planner_name);\n% plot path\nplot_path(path, G);\n% plot start and goal\nplot_square(start, map_size, G, \"#f00\");\nplot_square(goal, map_size, G, \"#15c\");\n% title\ntitle([planner_name, \"cost:\" + num2str(cost)]);\n\nhold off\n```\n\n# Version\n## Global Planner\n\nPlanner      |    Version    | Animation   \n------------ | --------- | --------- \n**GBFS**     | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/gbfs.m)     | ![gbfs_matlab.png](gif/gbfs_matlab.png)\n**Dijkstra**     | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/dijkstra.m) | ![dijkstra_matlab.png](gif/dijkstra_matlab.png)\n**A***     | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/a_star.m) | ![a_star.png](gif/a_star_matlab.png)\n**JPS**                 | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/jps.m) |  ![jps_matlab.png](gif/jps_matlab.png)\n**Theta\\***                 | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/theta_star.m) |  ![theta_star_matlab.png](gif/theta_star_matlab.png)\n**Lazy Theta\\***                 | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/lazy_theta_star.m) |  ![lazy_theta_star_matlab.png](gif/lazy_theta_star_matlab.png)\n**D***              |  [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/d_star.m) |  ![d_star_matlab.gif](gif/d_star_matlab.gif) \n**LPA***                 | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n**D\\* Lite**                 | ![Status](https://img.shields.io/badge/develop-v1.0-red) |![Status](https://img.shields.io/badge/gif-none-yellow)\n**Voronoi**                 | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/graph_search/voronoi_plan.m) |  ![voronoi_matlab.png](gif/voronoi_matlab.png)\n**RRT**                 | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/sample_search/rrt.m) | ![rrt_matlab.png](gif/rrt_matlab.png)\n**RRT***               | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/sample_search/rrt_star.m) |![rrt_star_matlab.png](gif/rrt_star_matlab.png)\n**Informed RRT**        | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/sample_search/informed_rrt.m) |![informed_rrt_matlab.png](gif/informed_rrt_matlab.png)\n**RRT-Connect**               | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/sample_search/rrt_connect.m) |![rrt_connect_matlab.png](gif/rrt_connect_matlab.png)\n\n## Local Planner\n| Planner |  Version    | Animation                                             |\n| ------- | -------------------------------------------------------- | -------------------------------------------------------- | \n| **PID**   | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/local_planner/pid_plan.m) | ![pid_matlab.gif](gif/pid_matlab.gif)\n|   **LQR**   |     [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/local_planner/lqr_plan.m)     | ![lqr_matlab.gif](gif/lqr_matlab.gif)\n|   **MPC**   |     [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/local_planner/mpc_plan.m)     | ![mpc_matlab.gif](gif/mpc_matlab.gif)\n| **APF**   | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/local_planner/apf_plan.m) | ![apf_matlab.gif](gif/apf_matlab.gif) \n| **DWA**  | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/local_planner/dwa_plan.m) | ![dwa_matlab.gif](gif/dwa_matlab.gif)\n|   **RPP**   |     [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/local_planner/rpp_plan.m)     | ![rpp_matlab.gif](gif/rpp_matlab.gif)\n| **TEB** | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n| **MPC** | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n| **Lattice** | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n\n## Intelligent Algorithm\n\n| Planner | Version    | Animation                                                 |\n| ------- | -------------------------------------------------------- | -------------------------------------------------------- \n| **ACO** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/global_planner/evolutionary_search/aco.m) | ![aco_matlab.png](gif/aco_matlab.png)\n| **GA**  | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n| **PSO** | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n| **ABC** | ![Status](https://img.shields.io/badge/develop-v1.0-red) | ![Status](https://img.shields.io/badge/gif-none-yellow) \n\n\n## Curve Generation\n\n| Planner | Version   | Animation                                |\n| ------- | -------------------------------------------------------- | -------------------------------------------------------- \n| **Polynomia** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/curve_generation/polynomial_curve.m) | ![polynomial_curve_matlab.png](gif/polynomial_curve_matlab.png)\n| **Bezier** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/curve_generation/bezier_curve.m) | ![bezier_curve_matlab.png](gif/bezier_curve_matlab.png)\n| **Cubic Spline** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/curve_generation/cubic_spline.m) | ![cubic_spline_curve_matlab.png](gif/cubic_spline_curve_matlab.png)\n| **BSpline** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/curve_generation/bspline_curve.m) | ![bspline_curve_matlab.png](gif/bspline_curve_matlab.png)\n| **Dubins** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/curve_generation/dubins_curve.m) | ![dubins_curve_matlab.png](gif/dubins_curve_matlab.png)\n| **Reeds-Shepp** | [![Status](https://img.shields.io/badge/done-v1.0-brightgreen)](https://github.com/ai-winter/matlab_motion_planning/blob/master/curve_generation/reeds_shepp.m) | ![reeds_shepp_curve_matlab.png](gif/reeds_shepp_curve_matlab.png)\n\n# Papers\n## Search-based Planning\n* [A*: ](https://ieeexplore.ieee.org/document/4082128) A Formal Basis for the heuristic Determination of Minimum Cost Paths\n* [JPS:](https://ojs.aaai.org/index.php/AAAI/article/view/7994) Online Graph Pruning for Pathfinding On Grid Maps\n* [Lifelong Planning A*: ](https://www.cs.cmu.edu/~maxim/files/aij04.pdf) Lifelong Planning A*\n* [D*: ](http://web.mit.edu/16.412j/www/html/papers/original_dstar_icra94.pdf) Optimal and Efficient Path Planning for Partially-Known Environments\n* [D* Lite: ](http://idm-lab.org/bib/abstracts/papers/aaai02b.pdf) D* Lite\n* [Theta*: ](https://www.jair.org/index.php/jair/article/view/10676) Theta*: Any-Angle Path Planning on Grids\n* [Lazy Theta*: ](https://ojs.aaai.org/index.php/AAAI/article/view/7566) Lazy Theta*: Any-Angle Path Planning and Path Length Analysis in 3D\n\n## Sample-based Planning\n* [RRT: ](http://msl.cs.uiuc.edu/~lavalle/papers/Lav98c.pdf) Rapidly-Exploring Random Trees: A New Tool for Path Planning\n* [RRT-Connect: ](http://www-cgi.cs.cmu.edu/afs/cs/academic/class/15494-s12/readings/kuffner_icra2000.pdf) RRT-Connect: An Efficient Approach to Single-Query Path Planning\n* [RRT*: ](https://journals.sagepub.com/doi/abs/10.1177/0278364911406761) Sampling-based algorithms for optimal motion planning\n* [Informed RRT*: ](https://arxiv.org/abs/1404.2334) Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal heuristic\n\n## Evolutionary-based Planning\n* [ACO: ](http://www.cs.yale.edu/homes/lans/readings/routing/dorigo-ants-1999.pdf) Ant Colony Optimization: A New Meta-Heuristic\n\n## Local Planning\n\n* [DWA: ](https://www.ri.cmu.edu/pub_files/pub1/fox_dieter_1997_1/fox_dieter_1997_1.pdf) The Dynamic Window Approach to Collision Avoidance\n* [APF: ](https://ieeexplore.ieee.org/document/1087247)Real-time obstacle avoidance for manipulators and mobile robots\n* [RPP: ](https://arxiv.org/pdf/2305.20026.pdf)Regulated Pure Pursuit for Robot Path Tracking\n\n## Curve Generation\n* [Dubins: ]() On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and 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