Path-Planning-for-a-differential-drive-robot-using-A-Star-Search-Algorithm

Introduction

The goal of this project is to implement a path planning algorithm for a rigid robot which uses A Star Search to find the goal node in the Configuration Space with Obstacles. The robot is a differential drive robot. In this case, a turtlebot is used.

Project Personnel

Team Members
Bharadwaj Chukkala
Joseph Pranadeer Reddy Katakam

Dependencies

Python 3.6
Matplotlib
Numpy
argparse
heapq

How to run the code

Clone the repository

git clone https://github.com/bharadwaj-chukkala/Path-Planning-for-a-differential-drive-robot-using-A-Star-Search-Algorithm.git

Open the terminal and navigate to the directory where the repository is cloned

cd Path-Planning-for-a-differential-drive-robot-using-A-Star-Search-Algorithm

To Run the following command to run the code for only visualization of the path
- Run the python script Phase2.py with the following command
```
python3 Phase2.py
```
- Enter the inputs as prompted in the terminal
- The path will be visualized in a plot after a few seconds.
To run the code for simulation of the robot in Gazebo through ROS:
- Copy paste the a_star_turtlebot package into the src folder of your catkin workspace
- Run the following commands in the terminal
```
cd ~/catkin_ws
catkin_make
source devel/setup.bash
roslaunch a_star_turtlebot proj.launch
```
- Enter the inputs as prompted in the terminal
- The robot will start moving towards the goal node
- To exit Gazebo press Ctrl+C in the terminal

Results

Phase 2 Part 1

This is the visualization of the path found by the A Star Search algorithm for a rigid robot which uses A Star Search to find the goal node in the Configuration Space with Obstacles. Click the below image to watch the video.

Phase 2 Part 2

This is the simulation of the above robot in Gazebo through ROS. Click the below image to watch the video.

Contact

Bharadwaj Chukkala
UID: 118341705
Bharadwaj Chukkala is currently a Master's student in Robotics at the University of Maryland, College Park, MD (Batch of 2023). His interests include Machine Learning, Perception and Path Planning.