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Title: GitHub - selfnature/PythonRobotics: Python sample codes for robotics algorithms.

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Description: Python sample codes for robotics algorithms. Contribute to selfnature/PythonRobotics development by creating an account on GitHub.

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[1808.10703] PythonRobotics: a Python code collection of robotics algorithms	https://arxiv.org/abs/1808.10703
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The Dynamic Window Approach to Collision Avoidance	https://www.ri.cmu.edu/pub_files/pub1/fox_dieter_1997_1/fox_dieter_1997_1.pdf
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	https://github.com/selfnature/PythonRobotics#grid-based-search
	https://github.com/selfnature/PythonRobotics#dijkstra-algorithm
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/Dijkstra/animation.gif
	https://github.com/selfnature/PythonRobotics#a-algorithm
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/AStar/animation.gif
	https://github.com/selfnature/PythonRobotics#potential-field-algorithm
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/PotentialFieldPlanning/animation.gif
Robotic Motion Planning:Potential Functions	https://www.cs.cmu.edu/~motionplanning/lecture/Chap4-Potential-Field_howie.pdf
	https://github.com/selfnature/PythonRobotics#grid-based-coverage-path-planning
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/GridBasedSweepCPP/animation.gif
	https://github.com/selfnature/PythonRobotics#state-lattice-planning
Optimal rough terrain trajectory generation for wheeled mobile robots	http://journals.sagepub.com/doi/pdf/10.1177/0278364906075328
State Space Sampling of Feasible Motions for High-Performance Mobile Robot Navigation in Complex Environments	http://www.frc.ri.cmu.edu/~alonzo/pubs/papers/JFR_08_SS_Sampling.pdf
	https://github.com/selfnature/PythonRobotics#biased-polar-sampling
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/StateLatticePlanner/BiasedPolarSampling.gif
	https://github.com/selfnature/PythonRobotics#lane-sampling
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/StateLatticePlanner/LaneSampling.gif
	https://github.com/selfnature/PythonRobotics#probabilistic-road-map-prm-planning
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/ProbabilisticRoadMap/animation.gif
Probabilistic roadmap - Wikipedia	https://en.wikipedia.org/wiki/Probabilistic_roadmap
	https://github.com/selfnature/PythonRobotics#rapidly-exploring-random-trees-rrt
	https://github.com/selfnature/PythonRobotics#rrt
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/RRTstar/animation.gif
Incremental Sampling-based Algorithms for Optimal Motion Planning	https://arxiv.org/abs/1005.0416
Sampling-based Algorithms for Optimal Motion Planning	http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.419.5503&rep=rep1&type=pdf
	https://github.com/selfnature/PythonRobotics#rrt-with-reeds-shepp-path
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/RRTStarReedsShepp/animation.gif
	https://github.com/selfnature/PythonRobotics#lqr-rrt
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/LQRRRTStar/animation.gif
LQR-RRT*: Optimal Sampling-Based Motion Planning with Automatically Derived Extension Heuristics	http://lis.csail.mit.edu/pubs/perez-icra12.pdf
MahanFathi/LQR-RRTstar: LQR-RRT* method is used for random motion planning of a simple pendulum in its phase plot	https://github.com/MahanFathi/LQR-RRTstar
	https://github.com/selfnature/PythonRobotics#quintic-polynomials-planning
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/QuinticPolynomialsPlanner/animation.gif
Local Path Planning And Motion Control For Agv In Positioning	http://ieeexplore.ieee.org/document/637936/
	https://github.com/selfnature/PythonRobotics#reeds-shepp-planning
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/ReedsSheppPath/animation.gif?raw=true
15.3.2 Reeds-Shepp Curves	http://planning.cs.uiuc.edu/node822.html
optimal paths for a car that goes both forwards and backwards	https://pdfs.semanticscholar.org/932e/c495b1d0018fd59dee12a0bf74434fac7af4.pdf
ghliu/pyReedsShepp: Implementation of Reeds Shepp curve.	https://github.com/ghliu/pyReedsShepp
	https://github.com/selfnature/PythonRobotics#lqr-based-path-planning
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/LQRPlanner/animation.gif?raw=true
	https://github.com/selfnature/PythonRobotics#optimal-trajectory-in-a-frenet-frame
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathPlanning/FrenetOptimalTrajectory/animation.gif
Optimal Trajectory Generation for Dynamic Street Scenarios in a Frenet Frame	https://www.researchgate.net/profile/Moritz_Werling/publication/224156269_Optimal_Trajectory_Generation_for_Dynamic_Street_Scenarios_in_a_Frenet_Frame/links/54f749df0cf210398e9277af.pdf
Optimal trajectory generation for dynamic street scenarios in a Frenet Frame	https://www.youtube.com/watch?v=Cj6tAQe7UCY
	https://github.com/selfnature/PythonRobotics#path-tracking
	https://github.com/selfnature/PythonRobotics#move-to-a-pose-control
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathTracking/move_to_pose/animation.gif
P. I. Corke, "Robotics, Vision and Control" \| SpringerLink p102	https://link.springer.com/book/10.1007/978-3-642-20144-8
	https://github.com/selfnature/PythonRobotics#stanley-control
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathTracking/stanley_controller/animation.gif
Stanley: The robot that won the DARPA grand challenge	http://robots.stanford.edu/papers/thrun.stanley05.pdf
Automatic Steering Methods for Autonomous Automobile Path Tracking	https://www.ri.cmu.edu/pub_files/2009/2/Automatic_Steering_Methods_for_Autonomous_Automobile_Path_Tracking.pdf
	https://github.com/selfnature/PythonRobotics#rear-wheel-feedback-control
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathTracking/rear_wheel_feedback/animation.gif
A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles	https://arxiv.org/abs/1604.07446
	https://github.com/selfnature/PythonRobotics#linearquadratic-regulator-lqr-speed-and-steering-control
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathTracking/lqr_speed_steer_control/animation.gif
Towards fully autonomous driving: Systems and algorithms - IEEE Conference Publication	http://ieeexplore.ieee.org/document/5940562/
	https://github.com/selfnature/PythonRobotics#model-predictive-speed-and-steering-control
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathTracking/model_predictive_speed_and_steer_control/animation.gif
notebook	https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/model_predictive_speed_and_steer_control/Model_predictive_speed_and_steering_control.ipynb
Real-time Model Predictive Control (MPC), ACADO, Python \| Work-is-Playing	http://grauonline.de/wordpress/?page_id=3244
	https://github.com/selfnature/PythonRobotics#nonlinear-model-predictive-control-with-c-gmres
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/PathTracking/cgmres_nmpc/animation.gif
notebook	https://github.com/AtsushiSakai/PythonRobotics/blob/master/PathTracking/cgmres_nmpc/cgmres_nmpc.ipynb
	https://github.com/selfnature/PythonRobotics#arm-navigation
	https://github.com/selfnature/PythonRobotics#n-joint-arm-to-point-control
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/ArmNavigation/n_joint_arm_to_point_control/animation.gif
	https://github.com/selfnature/PythonRobotics#arm-navigation-with-obstacle-avoidance
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/ArmNavigation/arm_obstacle_navigation/animation.gif
	https://github.com/selfnature/PythonRobotics#aerial-navigation
	https://github.com/selfnature/PythonRobotics#drone-3d-trajectory-following
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/AerialNavigation/drone_3d_trajectory_following/animation.gif
	https://github.com/selfnature/PythonRobotics#rocket-powered-landing
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/AerialNavigation/rocket_powered_landing/animation.gif
notebook	https://github.com/AtsushiSakai/PythonRobotics/blob/master/AerialNavigation/rocket_powered_landing/rocket_powered_landing.ipynb
	https://github.com/selfnature/PythonRobotics#bipedal
	https://github.com/selfnature/PythonRobotics#bipedal-planner-with-inverted-pendulum
	https://github.com/AtsushiSakai/PythonRoboticsGifs/raw/master/Bipedal/bipedal_planner/animation.gif
	https://github.com/selfnature/PythonRobotics#license
	https://github.com/selfnature/PythonRobotics#use-case
users_comments	https://github.com/AtsushiSakai/PythonRobotics/blob/master/users_comments.md
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our papers	https://arxiv.org/abs/1808.10703
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Atsushi Sakai	https://github.com/AtsushiSakai/
Daniel Ingram	https://github.com/daniel-s-ingram
Joe Dinius	https://github.com/jwdinius
Karan Chawla	https://github.com/karanchawla
Antonin RAFFIN	https://github.com/araffin
Alexis Paques	https://github.com/AlexisTM
Ryohei Sasaki	https://github.com/rsasaki0109
Göktuğ Karakaşlı	https://github.com/goktug97
Guillaume Jacquenot	https://github.com/Gjacquenot
Erwin Lejeune	https://github.com/guilyx
atsushisakai.github.io/PythonRobotics/	https://atsushisakai.github.io/PythonRobotics/
Readme	https://github.com/selfnature/PythonRobotics#readme-ov-file
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