// Spawns the agent facing towards it's goal tile.
public bool Spawn(Tile location)
{
path = AStarHelper.Calculate(location, Goal, speedPerFrame);
if (path == null
// TODO: Fix the issue with pathfinding that makes this necessary (without removing the occasional non-optimal paths if possible)
|| path.OfType <PathfindingMovement>().Sum(pm => Vector3.Distance(pm.Origin.Position, pm.Destination.Position)) > 4 * Vector3.Distance(location.Position, Goal.Position) ||
path.OfType <PathfindingDelay>().Any(pd => pd.Delay > 50))
{
//Debug.LogError(String.Format("Failed to find path from [{0},{1}] to [{2},{3}]!", location.X, location.Z, Goal.X, Goal.Z));
//Debug.DrawLine(location.Position, Goal.Position, Color.red, 5);
return(false);
}
agent = (GameObject)GameObject.Instantiate(model, location.Position, Quaternion.LookRotation(Goal.Position));
ClaimPath();
return(true);
}
// Calculate the A* path
public static List <IPathAction <T> > Calculate <T>(T start, T goal, float speed) where T : IPathNode <T>
{
List <T> closedset = new List <T>(); // The set of nodes already evaluated.
List <T> openset = new List <T>(); // The set of tentative nodes to be evaluated.
openset.Add(start);
Dictionary <T, T> cameFrom = new Dictionary <T, T>(); // The map of navigated nodes.
Dictionary <T, float> gScore = new Dictionary <T, float>();
gScore[start] = 0.0f; // Cost from start along best known path.
Dictionary <T, float> hScore = new Dictionary <T, float>();
hScore[start] = HeuristicCostEstimate(start, goal, speed);
Dictionary <T, float> fScore = new Dictionary <T, float>();
fScore[start] = hScore[start]; // Estimated total cost from start to goal through y.
while (openset.Count != 0)
{
T x = LowestScore(openset, fScore);
if (x.Equals(goal))
{
int time = 0;
List <IPathAction <T> > result = new List <IPathAction <T> >();
ReconstructPath(cameFrom, x, default(T), speed, ref result, ref time);
return(result);
}
openset.Remove(x);
closedset.Add(x);
foreach (T y in x.Connections)
{
if (AStarHelper.Invalid(y) || closedset.Contains(y))
{
continue;
}
float tentativeGScore = gScore[x] + Distance(x, y, (int)(gScore[x] / speed), speed);
bool tentativeIsBetter = false;
if (!openset.Contains(y))
{
openset.Add(y);
tentativeIsBetter = true;
}
else if (tentativeGScore < gScore[y])
{
tentativeIsBetter = true;
}
if (tentativeIsBetter)
{
cameFrom[y] = x;
gScore[y] = tentativeGScore;
hScore[y] = HeuristicCostEstimate(y, goal, speed);
fScore[y] = gScore[y] + hScore[y];
}
}
}
return(null);
}
