/// <summary>
/// Creates a path from the start voxel to some goal region, returning a list of movements that can
/// take a mover from the start voxel to the goal region.
/// </summary>
/// <param name="mover">The agent that we want to find a path for.</param>
/// <param name="startVoxel"></param>
/// <param name="goal">Goal conditions that the agent is trying to satisfy.</param>
/// <param name="chunks">The voxels that the agent is moving through</param>
/// <param name="maxExpansions">Maximum number of voxels to consider before giving up.</param>
/// <param name="toReturn">The path of movements that the mover should take to reach the goal.</param>
/// <param name="weight">
/// A heuristic weight to apply to the planner. If 1.0, the path is garunteed to be optimal. Higher values
/// usually result in faster plans that are suboptimal.
/// </param>
/// <param name="continueFunc"></param>
/// <returns>True if a path could be found, or false otherwise.</returns>
private static PlanResult Path(CreatureMovement mover, VoxelHandle startVoxel, GoalRegion goal, ChunkManager chunks,
int maxExpansions, ref List <MoveAction> toReturn, float weight, Func <bool> continueFunc)
{
// Create a local clone of the octree, using only the objects belonging to the player.
var octree = new OctTreeNode(mover.Creature.World.ChunkManager.Bounds.Min, mover.Creature.World.ChunkManager.Bounds.Max);
List <Body> playerObjects = new List <Body>(mover.Creature.World.PlayerFaction.OwnedObjects);
foreach (var obj in playerObjects)
{
octree.Add(obj, obj.GetBoundingBox());
}
var start = new MoveState()
{
Voxel = startVoxel
};
var startTime = DwarfTime.Tick();
if (mover.IsSessile)
{
return(new PlanResult()
{
Expansions = 0,
Result = PlanResultCode.Invalid,
TimeSeconds = DwarfTime.Tock(startTime)
});
}
// Sometimes a goal may not even be achievable a.priori. If this is true, we know there can't be a path
// which satisifies that goal.
if (!goal.IsPossible())
{
toReturn = null;
return(new PlanResult()
{
Expansions = 0,
Result = PlanResultCode.Invalid,
TimeSeconds = DwarfTime.Tock(startTime)
});
}
// Voxels that have already been explored.
var closedSet = new HashSet <MoveState>();
// Voxels which should be explored.
var openSet = new HashSet <MoveState>
{
start
};
// Dictionary of voxels to the optimal action that got the mover to that voxel.
var cameFrom = new Dictionary <MoveState, MoveAction>();
// Optimal score of a voxel based on the path it took to get there.
var gScore = new Dictionary <MoveState, float>();
// Expansion priority of voxels.
var fScore = new PriorityQueue <MoveState>();
// Starting conditions of the search.
gScore[start] = 0.0f;
fScore.Enqueue(start, gScore[start] + weight * goal.Heuristic(start.Voxel));
// Keep count of the number of expansions we've taken to get to the goal.
int numExpansions = 0;
// Check the voxels adjacent to the current voxel as a quick test of adjacency to the goal.
//var manhattanNeighbors = new List<VoxelHandle>(6);
//for (int i = 0; i < 6; i++)
//{
// manhattanNeighbors.Add(new VoxelHandle());
//}
// Loop until we've either checked every possible voxel, or we've exceeded the maximum number of
// expansions.
while (openSet.Count > 0 && numExpansions < maxExpansions)
{
if (numExpansions % 10 == 0 && !continueFunc())
{
return new PlanResult
{
Result = PlanResultCode.Cancelled,
Expansions = numExpansions,
TimeSeconds = DwarfTime.Tock(startTime)
}
}
;
// Check the next voxel to explore.
var current = GetStateWithMinimumFScore(fScore);
if (!current.IsValid)
{
// If there wasn't a voxel to explore, just try to expand from
// the start again.
numExpansions++;
continue;
}
numExpansions++;
// If we've reached the goal already, reconstruct the path from the start to the
// goal.
if (goal.IsInGoalRegion(current.Voxel) && cameFrom.ContainsKey(current))
{
toReturn = ReconstructPath(cameFrom, cameFrom[current], start);
return(new PlanResult()
{
Result = PlanResultCode.Success,
Expansions = numExpansions,
TimeSeconds = DwarfTime.Tock(startTime)
});
}
//Drawer3D.DrawLine(start.Voxel.GetBoundingBox().Center(), goal.GetVoxel().GetBoundingBox().Center(), Color.Red, 0.1f);
//Drawer3D.DrawBox(current.Voxel.GetBoundingBox(), Color.Red, 0.1f, true);
// We've already considered the voxel, so add it to the closed set.
openSet.Remove(current);
closedSet.Add(current);
IEnumerable <MoveAction> neighbors = null;
// Get the voxels that can be moved to from the current voxel.
neighbors = mover.GetMoveActions(current, octree).ToList();
//currentChunk.GetNeighborsManhattan(current, manhattanNeighbors);
var foundGoalAdjacent = neighbors.FirstOrDefault(n => !n.DestinationState.VehicleState.IsRidingVehicle && goal.IsInGoalRegion(n.DestinationState.Voxel));
// A quick test to see if we're already adjacent to the goal. If we are, assume
// that we can just walk to it.
if (foundGoalAdjacent.DestinationState.IsValid && foundGoalAdjacent.SourceState.IsValid)
{
if (cameFrom.ContainsKey(current))
{
List <MoveAction> subPath = ReconstructPath(cameFrom, foundGoalAdjacent, start);
toReturn = subPath;
return(new PlanResult()
{
Result = PlanResultCode.Success,
Expansions = numExpansions,
TimeSeconds = DwarfTime.Tock(startTime)
});
}
}
// Otherwise, consider all of the neighbors of the current voxel that can be moved to,
// and determine how to add them to the list of expansions.
foreach (MoveAction n in neighbors)
{
// If we've already explored that voxel, don't explore it again.
if (closedSet.Contains(n.DestinationState))
{
continue;
}
// Otherwise, consider the case of moving to that neighbor.
float tenativeGScore = gScore[current] + GetDistance(current.Voxel, n.DestinationState.Voxel, n.MoveType, mover);
// IF the neighbor can already be reached more efficiently, ignore it.
if (openSet.Contains(n.DestinationState) && !(tenativeGScore < gScore[n.DestinationState]))
{
continue;
}
// Otherwise, add it to the list of voxels for consideration.
openSet.Add(n.DestinationState);
// Add an edge to the voxel from the current voxel.
var cameAction = n;
cameFrom[n.DestinationState] = cameAction;
// Update the expansion scores for the next voxel.
gScore[n.DestinationState] = tenativeGScore;
fScore.Enqueue(n.DestinationState, gScore[n.DestinationState] + weight * (goal.Heuristic(n.DestinationState.Voxel) + (!n.DestinationState.VehicleState.IsRidingVehicle ? 100.0f : 0.0f)));
}
// If we've expanded too many voxels, just give up.
if (numExpansions >= maxExpansions)
{
return(new PlanResult()
{
Expansions = numExpansions,
Result = PlanResultCode.MaxExpansionsReached,
TimeSeconds = DwarfTime.Tock(startTime)
});
}
}
// Somehow we've reached this code without having found a path. Return false.
toReturn = null;
return(new PlanResult()
{
Expansions = numExpansions,
Result = PlanResultCode.NoSolution,
TimeSeconds = DwarfTime.Tock(startTime)
});
}
public List <MoveAction> ComputeGreedyFallback(int maxsteps = 10, List <VoxelHandle> exploredVoxels = null)
{
List <MoveAction> toReturn = new List <MoveAction>();
GoalRegion goal = GetGoal();
var creatureVoxel = Agent.Physics.CurrentVoxel;
if (goal.IsInGoalRegion(creatureVoxel))
{
return(toReturn);
}
var currentVoxel = creatureVoxel;
while (toReturn.Count < maxsteps)
{
var actions = Agent.Movement.GetMoveActions(new MoveState()
{
Voxel = currentVoxel
}, Creature.World.OctTree);
float minCost = float.MaxValue;
var minAction = new MoveAction();
bool hasMinAction = false;
foreach (var action in actions)
{
if (toReturn.Any(a => a.DestinationVoxel == action.DestinationVoxel && a.MoveType == action.MoveType))
{
continue;
}
var vox = action.DestinationVoxel;
float cost = goal.Heuristic(vox) * MathFunctions.Rand(1.0f, 1.1f) + Agent.Movement.Cost(action.MoveType);
if (exploredVoxels != null && exploredVoxels.Contains(action.DestinationVoxel))
{
cost *= 10;
}
if (cost < minCost)
{
minAction = action;
minCost = cost;
hasMinAction = true;
}
}
if (hasMinAction)
{
MoveAction action = minAction;
action.DestinationVoxel = currentVoxel;
toReturn.Add(action);
currentVoxel = minAction.DestinationVoxel;
if (goal.IsInGoalRegion(minAction.DestinationVoxel))
{
return(toReturn);
}
}
else
{
return(toReturn);
}
}
return(toReturn);
}
/// <summary>
/// Creates a path from the start voxel to some goal region, returning a list of movements that can
/// take a mover from the start voxel to the goal region.
/// </summary>
/// <param name="mover">The agent that we want to find a path for.</param>
/// <param name="start">The voxel that the agent starts in.</param>
/// <param name="goal">Goal conditions that the agent is trying to satisfy.</param>
/// <param name="chunks">The voxels that the agent is moving through</param>
/// <param name="maxExpansions">Maximum number of voxels to consider before giving up.</param>
/// <param name="toReturn">The path of movements that the mover should take to reach the goal.</param>
/// <param name="weight">
/// A heuristic weight to apply to the planner. If 1.0, the path is garunteed to be optimal. Higher values
/// usually result in faster plans that are suboptimal.
/// </param>
/// <returns>True if a path could be found, or false otherwise.</returns>
private static bool Path(CreatureMovement mover, Voxel start, GoalRegion goal, ChunkManager chunks,
int maxExpansions, ref List <Creature.MoveAction> toReturn, float weight)
{
// Sometimes a goal may not even be achievable a.priori. If this is true, we know there can't be a path
// which satisifies that goal.
if (!goal.IsPossible())
{
toReturn = null;
return(false);
}
// Voxels that have already been explored.
var closedSet = new HashSet <Voxel>();
// Voxels which should be explored.
var openSet = new HashSet <Voxel>
{
start
};
// Dictionary of voxels to the optimal action that got the mover to that voxel.
var cameFrom = new Dictionary <Voxel, Creature.MoveAction>();
// Optimal score of a voxel based on the path it took to get there.
var gScore = new Dictionary <Voxel, float>();
// Expansion priority of voxels.
var fScore = new PriorityQueue <Voxel>();
// Starting conditions of the search.
gScore[start] = 0.0f;
fScore.Enqueue(start, gScore[start] + weight * goal.Heuristic(start));
// Keep count of the number of expansions we've taken to get to the goal.
int numExpansions = 0;
// Check the voxels adjacent to the current voxel as a quick test of adjacency to the goal.
var manhattanNeighbors = new List <Voxel>(6);
for (int i = 0; i < 6; i++)
{
manhattanNeighbors.Add(new Voxel());
}
// Loop until we've either checked every possible voxel, or we've exceeded the maximum number of
// expansions.
while (openSet.Count > 0 && numExpansions < maxExpansions)
{
// Check the next voxel to explore.
Voxel current = GetVoxelWithMinimumFScore(fScore);
if (current == null)
{
// If there wasn't a voxel to explore, just try to expand from
// the start again.
current = start;
numExpansions++;
}
numExpansions++;
// If we've reached the goal already, reconstruct the path from the start to the
// goal.
if (goal.IsInGoalRegion(current))
{
// Assume that the last action in the path involves walking to the goal.
var first = new Creature.MoveAction
{
Voxel = current,
MoveType = Creature.MoveType.Walk
};
toReturn = ReconstructPath(cameFrom, first);
return(true);
}
// We've already considered the voxel, so add it to the closed set.
openSet.Remove(current);
closedSet.Add(current);
VoxelChunk currentChunk = chunks.ChunkData.ChunkMap[current.ChunkID];
List <Creature.MoveAction> neighbors = null;
// Get the voxels that can be moved to from the current voxel.
neighbors = mover.GetMoveActions(current);
currentChunk.GetNeighborsManhattan(current, manhattanNeighbors);
// A quick test to see if we're already adjacent to the goal. If we are, assume
// that we can just walk to it.
if (manhattanNeighbors.Contains(goal.GetVoxel()))
{
var first = new Creature.MoveAction
{
Voxel = current,
MoveType = Creature.MoveType.Walk
};
var last = new Creature.MoveAction
{
Voxel = goal.GetVoxel(),
MoveType = Creature.MoveType.Walk
};
List <Creature.MoveAction> subPath = ReconstructPath(cameFrom, first);
subPath.Add(last);
toReturn = subPath;
return(true);
}
// Otherwise, consider all of the neighbors of the current voxel that can be moved to,
// and determine how to add them to the list of expansions.
foreach (Creature.MoveAction n in neighbors)
{
// If we've already explored that voxel, don't explore it again.
if (closedSet.Contains(n.Voxel))
{
continue;
}
// Otherwise, consider the case of moving to that neighbor.
float tenativeGScore = gScore[current] + GetDistance(current, n.Voxel, n.MoveType, mover);
// IF the neighbor can already be reached more efficiently, ignore it.
if (openSet.Contains(n.Voxel) && !(tenativeGScore < gScore[n.Voxel]))
{
continue;
}
// Otherwise, add it to the list of voxels for consideration.
openSet.Add(n.Voxel);
// Add an edge to the voxel from the current voxel.
Creature.MoveAction cameAction = n;
cameAction.Voxel = current;
cameFrom[n.Voxel] = cameAction;
// Update the expansion scores for the next voxel.
gScore[n.Voxel] = tenativeGScore;
fScore.Enqueue(n.Voxel, gScore[n.Voxel] + weight * goal.Heuristic(n.Voxel));
}
// If we've expanded too many voxels, just give up.
if (numExpansions >= maxExpansions)
{
return(false);
}
}
// Somehow we've reached this code without having found a path. Return false.
toReturn = null;
return(false);
}
private static bool Path(CreatureMovement mover, Voxel start, GoalRegion goal, ChunkManager chunks, int maxExpansions, ref List <Creature.MoveAction> toReturn, bool reverse, float weight)
{
if (!goal.IsPossible())
{
toReturn = null;
return(false);
}
HashSet <Voxel> closedSet = new HashSet <Voxel>();
HashSet <Voxel> openSet = new HashSet <Voxel>
{
start
};
Dictionary <Voxel, Creature.MoveAction> cameFrom = new Dictionary <Voxel, Creature.MoveAction>();
Dictionary <Voxel, float> gScore = new Dictionary <Voxel, float>();
PriorityQueue <Voxel> fScore = new PriorityQueue <Voxel>();
gScore[start] = 0.0f;
fScore.Enqueue(start, gScore[start] + weight * goal.Heuristic(start));
int numExpansions = 0;
List <Voxel> manhattanNeighbors = new List <Voxel>(6);
for (int i = 0; i < 6; i++)
{
manhattanNeighbors.Add(new Voxel());
}
while (openSet.Count > 0 && numExpansions < maxExpansions)
{
Voxel current = GetVoxelWithMinimumFScore(fScore, openSet);
if (current == null)
{
current = start;
numExpansions++;
}
numExpansions++;
if (goal.IsInGoalRegion(current))
{
Creature.MoveAction first = new Creature.MoveAction()
{
Voxel = current,
MoveType = Creature.MoveType.Walk
};
toReturn = ReconstructPath(cameFrom, first);
return(true);
}
openSet.Remove(current);
closedSet.Add(current);
VoxelChunk currentChunk = chunks.ChunkData.ChunkMap[current.ChunkID];
List <Creature.MoveAction> neighbors = null;
neighbors = mover.GetMoveActions(current);
currentChunk.GetNeighborsManhattan(current, manhattanNeighbors);
if (manhattanNeighbors.Contains(goal.GetVoxel()))
{
Creature.MoveAction first = new Creature.MoveAction()
{
Voxel = current,
MoveType = Creature.MoveType.Walk
};
Creature.MoveAction last = new Creature.MoveAction()
{
Voxel = goal.GetVoxel(),
MoveType = Creature.MoveType.Walk
};
List <Creature.MoveAction> subPath = ReconstructPath(cameFrom, first);
subPath.Add(last);
toReturn = subPath;
return(true);
}
foreach (Creature.MoveAction n in neighbors)
{
if (closedSet.Contains(n.Voxel))
{
continue;
}
float tenativeGScore = gScore[current] + GetDistance(current, n.Voxel, n.MoveType, chunks);
if (openSet.Contains(n.Voxel) && !(tenativeGScore < gScore[n.Voxel]))
{
continue;
}
openSet.Add(n.Voxel);
Creature.MoveAction cameAction = n;
cameAction.Voxel = current;
cameFrom[n.Voxel] = cameAction;
gScore[n.Voxel] = tenativeGScore;
fScore.Enqueue(n.Voxel, gScore[n.Voxel] + weight * goal.Heuristic(n.Voxel));
}
if (numExpansions >= maxExpansions)
{
return(false);
}
}
toReturn = null;
return(false);
}