LuAstar, a simple A* pathfinding class
Posted: Thu Aug 04, 2011 1:02 pm
Hi,
I've been working on a implementing Astar pathfinding algorithm for a basic real time strategy I will start working on in a few.
Then I wanted to share the results it with all those who might be interested in.
I have used Patrick Lester tutorial (on Polyalmanac) on A-star pathfinding and Amit's A-star pages for theory learning purposes.
I don't pretend my implementation is the best, but i can consider this is a good job on the overall. It uses an internal node class (local to the libary) and provides you a set of functionnalities packed in a Lua table.
Plus, I have added some speed up tricks in the code for a quick computing.
- openList is not maintained in order. The code keeps track of the lowercost node each loop so that there is no need to skim trough the openList to find it.
- distance heuristic uses integers rather than the common squared root value to speed up computing on large maps.
A simple usage example:
A lot of metamethods are provided with this Astar class:
Any feedback, suggestions on how to improve, or wrong coded parts will be strongly appreciated.
Thanks in advance.
I've been working on a implementing Astar pathfinding algorithm for a basic real time strategy I will start working on in a few.
Then I wanted to share the results it with all those who might be interested in.
I have used Patrick Lester tutorial (on Polyalmanac) on A-star pathfinding and Amit's A-star pages for theory learning purposes.
I don't pretend my implementation is the best, but i can consider this is a good job on the overall. It uses an internal node class (local to the libary) and provides you a set of functionnalities packed in a Lua table.
Plus, I have added some speed up tricks in the code for a quick computing.
- openList is not maintained in order. The code keeps track of the lowercost node each loop so that there is no need to skim trough the openList to find it.
- distance heuristic uses integers rather than the common squared root value to speed up computing on large maps.
A simple usage example:
Code: Select all
--Assuming one wants to compute a path from cell (1,1) to cell ( 3,2) on a grid containing obstacles.
local Astar = require 'Lib.Astar'
Astar(map) -- inits the library
Astar:setObstValue(1) -- specifies that a value of 1 on the grid refers to an unwalkable location
Astar:setInitialNode(1,1)
Astar:setFinalNode(3,2)
local path = Astar:getPath()
A lot of metamethods are provided with this Astar class:
- setObstValue(value)
- getObstValue()
- enableDiagonalMove()
- disableDiagonalMove()
- setSearchDepth(value)
- getSearchDepth()
- setInitialNode()
- getInitialNode()
- setFinalNode()
- getFinalNode()
- isWalkable()
- getPath()
- reset()
Any feedback, suggestions on how to improve, or wrong coded parts will be strongly appreciated.
Thanks in advance.