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A star with Multiple objects path finding

  • itzvnodm
  • Oct 10, 2014
  • 2 min read

1. Created a square grid 20x20 nodes in size.

  • Randomly (and via the mouse) marked some of the nodes as "impassable or blocked".

  • Allowed each grid node to have a variable cost, via the mouse, 3 variations. For example, road tiles cost 1, forest tiles cost 2, water tiles cost 3.

  • Visualized the grid.

2. Created 10 game entities that navigate the grid in real-time.

  • Each entity chooses a random goal grid node as it's destination, perform an A* pathfind to that goal, and then travels along the calculated path to reach the goal. Each node's cost is accounted when path finding.

  • Each entity performs "seek"-like steering for the intermediate nodes along the path, and "arrival"-like steering for the goal node.

  • After each entity arrives (stops at) it's goal, it randomly chooses a new goal and keep going.

  • Allowed one entity to be "marked", to single it out for visualization. Visualized the 'start' and 'goal' nodes, it's current calculated path, and it's steering vector.

Start Node:

Start-Menu-Button.jpg

Goal Node:

finish.jpg

Impassable Node:

FD40138.jpg

Normal Node:

NomalTile.jpg

Forest Node: (Cost is 5, greater than normal node)

Forest.jpg

Water Node: (Cost is 10, greater than forest and normal node)

img.jpg

Hover Car: Uses A star algorithm to find the path to a next goal node in the scene randomly and performs seek / Arrive. The tile cost is taken in account when trying to find the path. Nodes with higher costs are avoided as much as possible. Preference is given in order,

Normal Node > Forest Node > Water Node

Hover Car.PNG

A * Algorithm used:

Astar.PNG

Heuristics will make the frontier expand towards the goal more than it expands in other directions.

Heuristics.PNG

 
 
 

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