This repository hosts the implementation of the paper "Online Obstacle evasion for Space-Filling Curves". The strategy is implemented in Python 3.11.5. Usage of conda environment for setuping and running the code is highly recommended. Steps to setup the code is described initially, while the file structure and files are described towards the end.

1. Install Conda using the official website. Conda Installation on Linux. Note : Use the instruction for your operating system.
2. Create a conda environment with Python 3.11.5

   conda create -n <env_name> python=3.11.5
   

<env_name> is the name of the conda environment. Any user defined name can be used, here SKC is used for the sake of example.

3. Activate the conda environment

   conda activate SKC
   

4. Install Dependencies

   a. igraph library for graph-related computations

   conda install -c conda-forge python-igraph=0.11.3
   

   b. Matplotlib for visualization

   conda install -c conda-forge matplotlib=3.8.2
   

   c. hilbertcurve for plotting Hilbert's curve

   conda install -c conda-forge hilbertcurve=2.0.5
   

5. Clone the repository

6. Activate the conda environment and open the cloned repository in it.

   conda activate SKC
   

   cd {clone location}/SKC
   

7. Run the code

   python3 main.py
   

8. Deactivate the conda

   conda deactivate SKC
   

File description :

• main.py : Source code for the project

• metric.py : Calculating and Plotting Metric for the proposed rerouting strategy

• Illustrations folder contains illustrations used in the paper