Dijkstra Algorithm

Hello readers!

When one wants to reach a place (destination) from it's starting point, it's quite obvious that he/she would like to trace a shorter path, and not a longer one eluding the neighboring obstacles. So, here we are discussing an algorithm which finds the shortest path between the starting point and the destination node in a given graph.

Typically, F=lia, where, lia is the shortest distance from the node i to the node a in the given network, and F is the sum between the distance start node and end node, and estimate as to how much distance is left to reach the goal location.

So, in this algorithm the nodes visits all the adjacent nodes, that it, it expands in all directions and the distance which is traversed from the initial node to the next node is compared with the previous parent node, and then the shortest distance is decided, this is the biggest disadvantage of Dijkstra Algorithm, that it does blind search, as it has to check all the nodes and compare the newly calculated tentative distance value to the current assigned value, and chose the smallest value. That is why it grows comparatively slow than to Astar algorithm. And other disadvantage is that, it can't work for negative edges.

As, it can be seen from the video that the colour map is as follows:

1. White - clear cell
2.  Black - obstacle
3. Red = visited
4. Blue  - on list
5. Green - startY
6. Yellow - destination

This was a course on Coursera, Computational Planning, the coding had to be done by oneself. We have done the coding on MATLAB.

Video of path planning algorithm: https://youtu.be/_V6-HSh5vDc