Path Planning Algorithms and Visualization in C++

Overview

This repository contains the C++ Implementation of Path Planning Algorithms of some common path planning algorithms used in robotics, including Search-based algorithms and Sampling-based algorithms based on the Python Implementation by Huiming Zhou. The algorithms can be visualized using the custom plotting class, which includes the generation of a new environment during each run for the grid-based planners, and an interactive dynamic environment developed to showcase dynamic algorithms. The related papers are listed in ZHM-REAL's original Python repository Papers.

Dependencies

The following dependencies are required to build and run the programs:

• OpenCV 2.4 or later: Install OpenCV from https://opencv.org/releases/ or use your package manager.
• ImageMagick++ (Magick++): Install ImageMagick++ from the official ImageMagick website or use your package manager. On many systems, installing libmagick++-dev (for Debian/Ubuntu) using sudo apt-get install libmagick++-dev or ImageMagick-c++-devel (for Red Hat/Fedora) using sudo dnf install ImageMagick-c++-devel should suffice.

Please make sure you have installed the required dependencies before compiling and running the programs.

Compilation and Build

Clone the repository:

git clone https://github.com/ahmedadamji/PathPlanning.git
cd PathPlanning

Make sure you have CMake installed. If not, install it from https://cmake.org/download/.

Create a build directory and navigate into it:

mkdir build
cd build

Run CMake to configure the build:

cmake ..

Build the project:

Running the Programs

Search_2D

To run the search-based algorithms (A*, Dijkstra, Best-First, etc.):

Open the terminal and navigate to the build directory.

Run the executable for the search_2D program:

./PathPlanning

The program will visualize the path planning algorithms on a 2D grid environment.

RRT_2D

To run the sampling-based algorithm (RRT-Connect):

Open the terminal and navigate to the build directory.

Run the executable for the rrt_2D program:

./SamplingBasedPlanning2D

The program will visualize the RRT-Connect algorithm on a 2D grid environment.

Note: In each main file, you can comment/uncomment the specific algorithm instantiation to choose which algorithm to run.

Animations - Search Based Planning

Animations - Sampling-Based

Acknowledgments

Thanks to Huiming Zhou for providing the original Python implementation and related papers for the path planning algorithms.