Path-planning-Demo : Overview of the grid search algorithm A* for global vessel path planning on cost map
This repository is a part of the diploma project at the Faculty of Electrical Engineering and Computing, University of Zagreb, Laboratory for Underwater Systems and Technologies. Repository is a predecessor of the diploma thesis repository Model-informed path planning and control for autonomous vessels and it is used for concept validation and testing of path planning A* algorithm on the 2D grid cost map. The algorithm is implemented in Python and uses the Pygame library for visualization.
git clone https://github.com/kr1zzo/Path-planning-Demo.git
pip install -r requirements/requirements.txt
To run the simulation, in the scripts folder execute the following command in the terminal:
python3 pathfinder.py- Press Tab to generate costmap
- Select the start and goal point by clicking on the map (left click)
- Add optional obstacles by clicking on the map (right click)
- Press start to run the path planning algorithm
Figure 1: Costmap generated by the path planning algorithm
Results and detailed project descriptions can be found in the documentation/report.pdf file. The report discusses how different cost map values and heuristic functions affect the path planning algorithm's performance for the different start and goal points. The report also discusses the algorithm's limitations and possible improvements.
Check out the Model-informed path planning and control for autonomous vessels repository for more advanced path planning algorithms and control strategies.
Figure 2: Example of A* path-planning between Rijeka and Baška, island Krk in Croatia
Contributors names and contact info
| Author | GitHub | |
|---|---|---|
| Enio Krizman | @kr1zzo | enio.krizman@fer.hr |
| Mentors | |
|---|---|
| Doc. Dr. Sc. Đula Nađ | dula.nad@fer.hr |
| Dr. Sc. Nadir Kapetanović | nadir.kapetanovi@fer.hr |