Pathfinding in Love2D usually refers to the process of navigating a character or entity through a map from one point to another, often avoiding obstacles and considering the shortest or most efficient route. The A* (A-Star) algorithm is a common choice for pathfinding because it's efficient and guarantees to find the shortest path if one exists.
Here's a high-level overview of how you might implement A* pathfinding in Love2D:
Define the grid: Your game world should be divided into a grid where each cell corresponds to a possible position an entity can occupy.
Identify walkable vs non-walkable tiles: Some grid cells will represent walls or obstacles and these need to be marked as non-walkable.
Implement the A algorithm:* At its core, A* checks adjacent cells (neighbors) and calculates the cost to move to those cells from the starting point, taking into account the estimated cost to reach the goal from there (heuristic).
function heuristic(a, b) -- Manhattan distance on a square grid return math.abs(a.x - b.x) + math.abs(a.y - b.y) end function isInTable(tbl, item) for key, value in pairs(tbl) do if value == item then return true end end return false end function aStar(start, goal, map) local openSet = {[start] = true} local cameFrom = {} local gScore, fScore = {}, {} gScore[start] = 0 fScore[start] = heuristic(start, goal) while next(openSet) do local current = nil for node, _ in pairs(openSet) do if current == nil or fScore[node] < fScore[current] then current = node end end if current == goal then local path = {} while current do table.insert(path, 1, current) current = cameFrom[current] end return path end openSet[current] = nil for _, neighbor in ipairs(map:getNeighbors(current)) do if map:isWalkable(neighbor) then local tentative_gScore = gScore[current] + heuristic(current, neighbor) if gScore[neighbor] == nil or tentative_gScore < gScore[neighbor] then cameFrom[neighbor] = current gScore[neighbor] = tentative_gScore fScore[neighbor] = gScore[neighbor] + heuristic(neighbor, goal) if not isInTable(openSet, neighbor) then openSet[neighbor] = true end end end end end return nil -- no path found end
Create map
object methods: In the example above, map:getNeighbors(node)
should return a list of walkable neighbor nodes for the specified node
, and map:isWalkable(node)
should return whether a node is walkable.
Call the aStar
function: When you want to find a path, call aStar(start, goal, map)
with the start and goal nodes along with the map object as parameters.
Please note that this code is a very simplified example to illustrate the concept, and it assumes we have a map
object which has knowledge about the grid, including whether a given node is walkable and who the neighbors are. In practice, your implementation would likely be more complex, especially in terms of how you represent the map and interact with the rest of your game's systems.
Considerations when implementing:
Implementing pathfinding can be quite complex and requires careful consideration of how it interacts with the rest of your game's logic and performance requirements.
Dragonfly is fully compatible with the Redis ecosystem and requires no code changes to implement.