Implementation-of-Dijkstra-Path-Planning-Algorithm

Instructions:

• Clone the repository to your local machine using the following command:

  git clone https://github.com/stark-2000/Implementation-of-Dijkstra-Path-Planning-Algorithm.git
  

  cd into the cloned repository

  cd Implementation-of-Dijkstra-Path-Planning-Algorithm
  

• Alternatively, you can download the zip file of the repository and extract it to your local machine:

  cd proj2_dhinesh_rajasekaran
  

• Open Terminal and Run the following commands & test with the following test cases: (make sure visulization.py file is in the same folder)

  python3 dijkstra_Dhinesh_Rajasekaran.py
  

• Now for Test Case 1, Enter the following values when prompted or any random values of your choice:

  • Enter the start node as "20,20"
  • Enter the goal node as "425,200"

• Repeat the above step for Test Case 2 with the following values or random values of your choice:

  • Enter the start node as "50,43"
  • Enter the goal node as "250,30"

Obstacle Space - Map:

• Adobe Photoshop generated:

• Desmos Visualization:

Demo Video:

• Video shows exploration of nodes and finding the goal node for a point robot given start & goal nodes. Once the shortest path is found, it is backtracked and visualized using openCV.

Animation_Video_Output.mp4

Dependencies:

• visulization.py file (map creation and visualization script)

  • It is already included in the repository in the same folder. Make sure you are running dijkstra_Dhinesh_Rajasekaran.py script from the same folder.

• Numpy library

  • if req open terminal and run the following commands

  sudo pip install numpy
  

• openCV library

  • if req open terminal and run the following commands

  sudo pip install opencv-contrib-python
  

• time library

  • if req open terminal and run the following commands

  sudo pip install time
  

• heapq library

  • if req open terminal and run the following commands

  sudo pip install heapq