Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/zhm-real/MotionPlanning

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)
https://github.com/zhm-real/MotionPlanning

autonomous-vehicles frenet-frames front-wheel-feedback hybrid-astar lqr motion-planning-algorithms mpc path-tracking pathplanning pure-pursuit rear-wheel-feedback stanley stanley-controller state-lattice-planner tracking

Last synced: about 1 month ago
JSON representation

Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking)

Host: GitHub
URL: https://github.com/zhm-real/MotionPlanning
Owner: zhm-real
Created: 2020-07-08T19:12:46.000Z (almost 4 years ago)
Default Branch: master
Last Pushed: 2024-01-13T06:05:01.000Z (5 months ago)
Last Synced: 2024-02-04T05:41:13.478Z (4 months ago)
Topics: autonomous-vehicles, frenet-frames, front-wheel-feedback, hybrid-astar, lqr, motion-planning-algorithms, mpc, path-tracking, pathplanning, pure-pursuit, rear-wheel-feedback, stanley, stanley-controller, state-lattice-planner, tracking
Language: Python
Homepage: https://github.com/zhm-real/MotionPlanning
Size: 22.8 MB
Stars: 1,716
Watchers: 27
Forks: 511
Open Issues: 3
Metadata Files:
- Readme: README.md

Lists

Awesome-Self-Driving - MotionPlanning - Motion planning algorithms commonly used on autonomous vehicles. (path planning + path tracking). (2. Planning)
awesome-mobile-robotics - Motion planners implementations

README

        ## Overview

This repository implemented some common motion planners used on autonomous vehicles, including

* [Hybrid A* Planner](https://ai.stanford.edu/~ddolgov/papers/dolgov_gpp_stair08.pdf)

* [Frenet Optimal Trajectory](https://www.researchgate.net/publication/224156269_Optimal_Trajectory_Generation_for_Dynamic_Street_Scenarios_in_a_Frenet_Frame)

* [Hierarchical Optimization-Based Collision Avoidance (H-OBCA)](https://ieeexplore.ieee.org/document/9062306) (Incomplete)

Also, this repository provides some controllers for path tracking, including

* [Pure Pursuit + PID](https://www.ri.cmu.edu/pub_files/pub3/coulter_r_craig_1992_1/coulter_r_craig_1992_1.pdf)

* [Rear-Wheel Feedback + PID](https://www.ri.cmu.edu/pub_files/2009/2/Automatic_Steering_Methods_for_Autonomous_Automobile_Path_Tracking.pdf)

* [Front-Wheel Feedback / Stanley + PID](http://robots.stanford.edu/papers/thrun.stanley05.pdf)

* [LQR + PID](https://github.com/ApolloAuto/apollo/tree/master/modules/control/controller)

* [Linear MPC](https://borrelli.me.berkeley.edu/pdfpub/pub-6.pdf)

## Requirement

* Python 3.6 or above

* [SciPy](https://www.scipy.org/)

* [cvxpy](https://github.com/cvxgrp/cvxpy)

* [Reeds-Shepp Curves](https://github.com/zhm-real/ReedsSheppCurves)

* [pycubicspline](https://github.com/AtsushiSakai/pycubicspline)

## Vehicle models

This repository uses two models: simple car model and [car pulling trailers model](http://planning.cs.uiuc.edu/node661.html#77556).

## Hybrid A* Planner



  

    

    

  

  

    

    

  

  

    

    

  



## State Lattice Planner



  

    

    

  



## Controllers



  

    

    

  

  

    

    

  

  

    

    

  



## Paper

### Planning

* [Basic Path Planning Algorithms: ](https://github.com/zhm-real/PathPlanning) PathPlanning

* [Baidu Apollo Planning module: ](https://github.com/ApolloAuto/apollo/tree/master/modules/planning) Recommended Materials

* [Survey of Planning and Control algos: ](https://arxiv.org/pdf/1604.07446.pdf) A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles

* [Hybrid A* Planner: ](https://ai.stanford.edu/~ddolgov/papers/dolgov_gpp_stair08.pdf) Practical Search Techniques in Path Planning for Autonomous Driving

* [Frenet Optimal Trajectory: ](https://www.researchgate.net/publication/224156269_Optimal_Trajectory_Generation_for_Dynamic_Street_Scenarios_in_a_Frenet_Frame) Optimal Trajectory Generation for Dynamic Street Scenarios in a Frenet Frame

### Control

* [Baidu Apollo Control module: ](https://github.com/ApolloAuto/apollo/tree/master/modules/control) Recommended Materials

* [Pure Pursuit: ](https://www.ri.cmu.edu/pub_files/pub3/coulter_r_craig_1992_1/coulter_r_craig_1992_1.pdf) Implementation of the Pure Pursuit Path Tracking Algorithm 

* [Rear-Wheel Feedback: ](https://www.ri.cmu.edu/pub_files/2009/2/Automatic_Steering_Methods_for_Autonomous_Automobile_Path_Tracking.pdf) Automatic Steering Methods for Autonomous Automobile Path Tracking

* [Front-Wheel Feedback / Stanley: ](http://robots.stanford.edu/papers/thrun.stanley05.pdf) Stanley: The Robot that Won the DARPA Grand Challenge

* [LQR: ](https://github.com/ApolloAuto/apollo/tree/master/modules/control/controller) ApolloAuto/apollo: An open autonomous driving platform

* [Linear MPC: ](https://borrelli.me.berkeley.edu/pdfpub/pub-6.pdf) MPC-Based Approach to Active Steering for Autonomous Vehicle Systems

## Useful Material

* [HybridAStarTrailer (Julia): ](https://github.com/AtsushiSakai/HybridAStarTrailer) by AtsushiSakai

* [Hybrid Path Planner (C++): ](https://github.com/karlkurzer/path_planner) by KTH Research Concept Vehicle