Bringing Pathfinding Algorithms to Life with an Interactive UI

Pathfinding algorithms have long been an essential tool in fields such as robotics, video game development, and transportation planning.

With the goal of making these algorithms more accessible and understandable to the public, I recently implemented multiple pathfinding algorithms such as Dijkstra’s and Depth-First Search, and built an interactive user interface to visually demonstrate their process. You can check it out here

What is Dijkstra?

The Dijkstra algorithm is a popular algorithm for finding the shortest path between two nodes in a weighted graph. It works by maintaining a priority queue of unvisited nodes, with the node with the shortest distance from the source node being at the top of the queue. The algorithm then explores the neighboring nodes of the current node and updates their distances if a shorter path is found. This process continues until the destination node is reached or there are no more nodes to explore.

Here are the steps of the Dijkstra algorithm:

Initialize all nodes as unvisited and set their distances to infinity, except for the source node which is set to 0.

Create a priority queue and add the source node to it with a distance of 0.

While the priority queue is not empty, remove the node with the shortest distance from the queue.

For each neighboring node of the current node, calculate the distance from the source node via the current node.

If the new distance is shorter than the current distance, update the distance of the neighboring node and add it to the priority queue.

Repeat previous three steps until the destination node is removed from the priority queue, or the priority queue is empty.

Once the algorithm is complete, the shortest distance to the destination node is the distance stored in the node, and the shortest path can be found by backtracking from the destination node to the source node using the recorded distances.

What is the DFS?

The DFS algorithm, or Depth-First Search, is a popular algorithm for traversing a graph or tree data structure. It starts at a given node and explores as far as possible along each branch before backtracking. The algorithm maintains a stack to keep track of the nodes to visit, and a set to keep track of the visited nodes.

Here are the steps of the DFS algorithm:

Select a starting node and mark it as visited.

Push the starting node onto a stack.

While the stack is not empty, pop a node from the top of the stack.

For each unvisited neighbor of the current node, mark it as visited and push it onto the stack.

Repeat previous two steps until the stack is empty.

The interface I implemented ..

allows users to choose different algorithms, draw walls, and drag and drop the starting and finishing points. This provides a hands-on visualization of the pathfinding process and enables users to see how each algorithm finds the shortest or any path between two points on a grid.

In addition to the interactive elements, I included a "Create Random Walls" button that dynamically generates barriers on the grid. This allows users to increase the level of difficulty and showcases the versatility of the pathfinding algorithms.

Overall, this project has been a rewarding experience, not only for the insights it has provided me about pathfinding algorithms, but also for the potential it has to make these complex concepts more accessible and understandable to others.

Reach out anytime!👋

Ulugbek Nurmatov

Bringing Pathfinding Algorithms to Life with an Interactive UI

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Reach out anytime!👋

Ulugbek Nurmatov

Bringing Pathfinding Algorithms to Life with an Interactive UI

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