# PythonRobotics Python sample codes for robotics algorithm. # Requirements - numpy - scipy - matplotlib - [pyReedsShepp](https://github.com/ghliu/pyReedsShepp) (Only for reeds sheep path and RRTStarCar_reeds_sheep) # Path Planning Path planning algorithm. ## Model Predictive Trajectory Generator This script is a path planning code with model predictive trajectory generator. ### Path optimization sample: ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/ModelPredictiveTrajectoryGenerator/kn05animation.gif) ### Lookup table generation sample: ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/ModelPredictiveTrajectoryGenerator/lookuptable.png?raw=True) see: - [Optimal rough terrain trajectory generation for wheeled mobile robots](http://journals.sagepub.com/doi/pdf/10.1177/0278364906075328) 　 ## State Lattice Planning This script is a path planning code with state lattice planning. This code uses the model predictive trajectory generator to solve boundary problem. ### Uniform polar sampling results: ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/StateLatticePlanner/Figure_1.png) ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/StateLatticePlanner/Figure_2.png) ### Biased polar sampling results: ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/StateLatticePlanner/Figure_3.png) ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/StateLatticePlanner/Figure_4.png) ### Lane sampling results: ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/StateLatticePlanner/Figure_5.png) ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/StateLatticePlanner/Figure_6.png) ## RRT Rapidly Randamized Tree Path planning sample. ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/RRT/animation.gif) This script is a simple path planning code with Rapidly-Exploring Random Trees (RRT) see (in Japanese) : [PythonによるRapidly-Exploring Random Trees (RRT)パスプランニングサンプルプログラム - MyEnigma](http://myenigma.hatenablog.com/entry/2016/03/23/092002) ## RRTStar ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/RRTstar/animation.gif) This script is a path planning code with RRT \* - [Incremental Sampling-based Algorithms for Optimal Motion Planning](https://arxiv.org/abs/1005.0416) ## RRT Car ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/RRTCar/animation.gif) Path planning for a car robot with RRT and dubins path planner. ## RRTStarCar ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/RRTStarCar/animation.gif) Path planning for a car robot with RRT\* and dubings path planner. ## RRTStarCar_reeds_sheep ![Robotics/animation.gif at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/RRTStarCar_reeds_sheep/animation.gif)) Path planning for a car robot with RRT\* and reeds sheep path planner. ## Dubins path planning A sample code for Dubins path planning. [Dubins path - Wikipedia](https://en.wikipedia.org/wiki/Dubins_path) ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/DubinsPath/figures/figure_1.png?raw=True) ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/DubinsPath/figures/figure_13.png?raw=True) ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/DubinsPath/figures/figure_15.png?raw=True) ## Reeds Shepp planning A sample code with Reeds Shepp path planning. ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/ReedsSheppPath/figure_1-4.png?raw=true) ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/ReedsSheppPath/figure_1-5.png?raw=true) ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/ReedsSheppPath/figure_1-7.png?raw=true) ## Closed Loop RRT\* A sample code with closed loop RRT\*. ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/CRRRTStar/Figure_1.png?raw=True) ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/CRRRTStar/Figure_4.png?raw=True) ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathPlanning/CRRRTStar/Figure_5.png?raw=True) see: - [Motion Planning in Complex Environments using Closed-loop Prediction](http://acl.mit.edu/papers/KuwataGNC08.pdf) - [Real-time Motion Planning with Applications to Autonomous Urban Driving](http://acl.mit.edu/papers/KuwataTCST09.pdf) - [[1601.06326] Sampling-based Algorithms for Optimal Motion Planning Using Closed-loop Prediction](https://arxiv.org/abs/1601.06326) # Path tracking Path tracking algorithm samples. ## Pure pursuit tracking Path tracking simulation with pure pursuit steering control and PID speed control. ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/pure_pursuit/Figure_1-3.png?raw=True) ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/pure_pursuit/2Figure_1-2.png?raw=True) ![PythonRobotics/figure_1-5.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/pure_pursuit/4Figure_1-2.png?raw=True) ## Rear wheel feedback control Path tracking simulation with rear wheel feedback steering control and PID speed control. ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/rear_wheel_feedback/animation.gif) ## Linear–quadratic regulator (LQR) control Path tracking simulation with LQR steering control and PID speed control. ![PythonRobotics/figure_1.png at master · AtsushiSakai/PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/lqr/animation.gif) # License MIT # Author Atsushi Sakai ([@Atsushi_twi](https://twitter.com/Atsushi_twi))