https://github.com/onlytailei/CppRobotics

cpp implementation of robotics algorithms including localization, mapping, SLAM, path planning and control
https://github.com/onlytailei/CppRobotics

algorithms cpp localization planning robotics

Last synced: 3 months ago
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cpp implementation of robotics algorithms including localization, mapping, SLAM, path planning and control

• Host: GitHub
• URL: https://github.com/onlytailei/CppRobotics
• Owner: onlytailei
• License: mit
• Created: 2019-03-28T07:09:18.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2024-03-08T13:25:58.000Z (8 months ago)
• Last Synced: 2024-05-08T10:32:11.859Z (6 months ago)
• Topics: algorithms, cpp, localization, planning, robotics
• Language: C++
• Homepage:
• Size: 6.43 MB
• Stars: 1,731
• Watchers: 58
• Forks: 478
• Open Issues: 6
• Metadata Files:
  • Readme: readme.md
  • License: LICENSE.md

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README

        
# CppRobotics

This is the cpp implementation of the [PythonRobotics](https://github.com/AtsushiSakai/PythonRobotics)

## Requirment

- cmake

- opencv 3.3

- Eigen 3

- [CppAD](https://www.coin-or.org/CppAD/Doc/install.htm) / [IPOPT](https://www.coin-or.org/Ipopt/documentation/node14.html) (*for MPC convex optimization*) [install tips](https://github.com/udacity/CarND-MPC-Quizzes/blob/master/install_Ipopt_CppAD.md)

- ~~ROS~~ (*~~To make the repo lightweight :)~~. Yet, we may still need it for 3D visualization.*)

## Build

     $ mkdir build

     $ cd build

     $ cmake ../

     $ make -j 8

Find all the executable files in ***build/bin***.

# Table of Contents

* [Localization](#localization)

    * [Extended kalmam filter](#extended-kalman-filter-localization)

    * [Particle filter](#particle-filter-localization)

    * Histogram filter

* [Mapping](#mapping)

    * Gaussian grid map

* [SLAM](#SLAM)

    * FastSLAM 1.0

* [Path Planning](#path-planning)

    * [Dijkstra](#dijkstra)

    * [A Star](#a-star)

    * [RRT](#rrt)

    * [Dynamic Window Approach](#dynamic-window-approach)

    * [Model Predictive Trajectory Generator](#model-predictive-trajectory-generator)

    * [Cubic Spline Planner](#cubic-spline-planner)

    * [State Lattice Planner](#state-lattice-planner)

    * [Frenet Frame Trajectory](#frenet-frame-trajectory)

* [Path Tracking Control](#path-tracking-control)

    * [LQR Sterring Control](#lqr-steering-control)

    * [LQR Speed and Steering Control](#lqr-speed-and-steering-control)

    * [Model Predictive Speed and Steering Control](#mpc-speed-and-steering-control)

* [Aerial Navigation](#aerial-navigation)

     * Drone 3D Trajectory Following

     * Rocket Powered Landing

# Localization

## Extended Kalman Filter Localization

* green line: the groundtruth trajectory

* black line: dead reckoning

* red points: observations (e.g. GPS)

* blue line: estimated positions



[Probabilistic Robotics](http://www.probabilistic-robotics.org/)

## Particle Filter Localization

* green line: the groundtruth trajectory

* black line: dead reckoning

* red points: landmarks

* blue line: estimated positions



[Probabilistic Robotics](http://www.probabilistic-robotics.org/)

# Path Planning

## Dijkstra

* blue point: the start point

* red point: the goal point



## A star

* blue point: the start point

* red point: the goal point



## RRT

* red circle: the start point

* blue circle: the goal point

* black circle: obstacles



## Dynamic Window Approach

* blue circle: the target point

* red circle: the robot



[The dynamic window approach to collision avoidance](https://ieeexplore.ieee.org/document/580977)

## Model Predictive Trajectory Generator

This part is based on the bicycle motion model.

* blue circle: the target point

* red circle: the initial point



## Cubic Spline Planner



## State Lattice Planner

* blue circle: the target point

* red circle: the initial point



[State Space Sampling of Feasible Motions for High-Performance Mobile Robot Navigation in Complex Environments](https://www.ri.cmu.edu/pub_files/pub4/howard_thomas_2008_1/howard_thomas_2008_1.pdf)

## Frenet Frame Trajectory

* black line: the planned spline path

* red circle: the obstacle

* blue circle: the planned trajectory

* green circle: the real-time position of robot



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

# Path Tracking Control

## LQR Steering Control

* black line: the planned spline path

* red circle: the position under lqr control



## LQR Speed and Steering Control

* black line: the planned spline path

* red circle: the position under lqr control



## MPC Speed and Steering Control

* black line: the planned spline path

* blue line: the passed path

* yellow cross: the reference trajectory for MPC    

(To compile this part, you need to uncomment the related lines in CMakeLists.txt and install [CppAD](https://www.coin-or.org/CppAD/Doc/install.htm) and [IPOPT](https://coin-or.github.io/Ipopt/).)