Trailblazer - Team 25

Determines an optimal travelling path for space exploration.

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https://drive.google.com/drive/u/0/folders/1OFxaGXrc9eR3aO2AC-NQjFJyax8CxFzS

Inspiration

With so much recent news about space exploration, we wanted to try and build something that could be useful on the surface of other planets.

What it does

Trailblazer takes a topographical map and allows you to find the shortest path between any two points within the map. It takes into account differences in elevation to reduce the amount of work required to get from one place to the next. This is optimal for space exploration where the minimization of energy usage is crucial.

How we built it

We used Python to build both the GUI and the algorithm that is the basis of Trailblazer. The specific algorithm we used is a modified version of the A* path finding algorithm.

Challenges we ran into

Determining and programming an optimal algorithm to determine the shortest path was quite difficult and required a lot of thought.

Accomplishments that we're proud of

We are very proud of the performance of the software since it creates visibly shorter paths than a straight line to the destination. The program is also very flexible since you can input different start and end points and different parameters for the scaling of the input map.

What we learned

We learned a lot of interesting algorithms while researching how to achieve our project's goal and also learned how to get a GUI up and running.

What's next for Trailblazer

In the future, we aim to make the algorithm even more efficient and improve on the GUI to create a better user experience.

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