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• Tile-wide extent tracing on a grid.

  - by Larolaro

  I'm currently working on A* pathfinding on a grid and I'm looking to smooth the generated path, while also considering the extent of the character moving along it. I'm using a grid for the pathfinding, however character movement is free roaming, not strict tile to tile movement. To achieve a smoother, more efficient path, I'm doing line traces on a grid to determine if there is unwalkable tiles between tiles to shave off unecessary corners. However, because a line trace is zero extent, it doesn't consider the extent of the character and gives bad results (not returning unwalkable tiles just missed by the line, causing unwanted collisions). So what I'm looking for is rather than a line algorithm that determines the tiles under it, I'm looking for one that determines the tiles under a tile-wide extent line. Here is an image to help visualise my problem! Does anyone have any ideas? I've been working with Bresenham's line and other alternatives but I haven't yet figured out how to nail this specific problem.

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• Pathfinding for fleeing

  - by Philipp

  As you know there are plenty of solutions when you wand to find the best path in a 2-dimensional environment which leads from point A to point B. But how do I calculate a path when an object is at point A, and wants to get away from point B, as fast and far as possible? A bit of background information: My game uses a 2d environment which isn't tile-based but has floating point accuracy. The movement is vector-based. The pathfinding is done by partitioning the game world into rectangles which are walkable or non-walkable and building a graph out of their corners. I already have pathfinding between points working by using Dijkstras algorithm. The use-case for the fleeing algorithm is that in certain situations, actors in my game should perceive another actor as a danger and flee from it. The trivial solution would be to just move the actor in a vector in the direction which is opposite from the threat until a "safe" distance was reached or the actor reaches a wall where it then covers in fear. The problem with this approach is that actors will be blocked by small obstacles they could easily get around. As long as moving along the wall wouldn't bring them closer to the threat they could do that, but it would look smarter when they would avoid obstacles in the first place: Another problem I see is with dead ends in the map geometry. In some situations a being must choose between a path which gets it faster away now but ends in a dead end where it would be trapped, or another path which would mean that it wouldn't get that far away from the danger at first (or even a bit closer) but on the other hand would have a much greater long-term reward in that it would eventually get them much further away. So the short-term reward of getting away fast must be somehow valued against the long-term reward of getting away far. There is also another rating problem for situations where an actor should accept to move closer to a minor threat to get away from a much larger threat. But completely ignoring all minor threats would be foolish, too (that's why the actor in this graphic goes out of its way to avoid the minor threat in the upper right area): Are there any standard solutions for this problem?

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• Contricted A* problem

  - by Ragekit

  I've got a little problem with an A* algorithm that I need to constrict a little bit. Basically : I use an A* to find the shortest path between 2 randomly placed room in 3D space, and then build a corridor between them. The problem I found is that sometimes it makes chimney like corridors that are not ideal, so I constrict the A* so that if the last movement was up or down, you go sideways. Everything is fine, but in some corner cases, it fails to find a path (when there is obviously one). Like here between the blue and red dot : (i'm in unity btw, but i don't think it matters) Here is the code of the actual A* (a bit long, and some redundency) while(current != goal) { //add stair up / stair down foreach(Node<GridUnit> test in current.Neighbors) { if(!test.Data.empty && test != goal) continue; //bug at arrival; if(test == goal && penul !=null) { Vector3 currentDiff = current.Data.bounds.center - test.Data.bounds.center; if(!Mathf.Approximately(currentDiff.y,0)) { //wanna drop on the last if(!coplanar(test.Data.bounds.center,current.Data.bounds.center,current.Data.parentUnit.bounds.center,to.Data.bounds.center)) { continue; } else { if(Mathf.Approximately(to.Data.bounds.center.x, current.Data.parentUnit.bounds.center.x) && Mathf.Approximately(to.Data.bounds.center.z, current.Data.parentUnit.bounds.center.z)) { continue; } } } } if(current.Data.parentUnit != null) { Vector3 previousDiff = current.Data.parentUnit.bounds.center - current.Data.bounds.center; Vector3 currentDiff = current.Data.bounds.center - test.Data.bounds.center; if(!Mathf.Approximately(previousDiff.y,0)) { if(!Mathf.Approximately(currentDiff.y,0)) { //you wanna drop now : continue; } if(current.Data.parentUnit.parentUnit != null) { if(!coplanar(test.Data.bounds.center,current.Data.bounds.center,current.Data.parentUnit.bounds.center,current.Data.parentUnit.parentUnit.bounds.center)) { continue; }else { if(Mathf.Approximately(test.Data.bounds.center.x, current.Data.parentUnit.parentUnit.bounds.center.x) && Mathf.Approximately(test.Data.bounds.center.z, current.Data.parentUnit.parentUnit.bounds.center.z)) { continue; } } } } } g = current.Data.g + HEURISTIC(current.Data,test.Data); h = HEURISTIC(test.Data,goal.Data); f = g + h; if(open.Contains(test) || closed.Contains(test)) { if(test.Data.f > f) { //found a shorter path going passing through that point test.Data.f = f; test.Data.g = g; test.Data.h = h; test.Data.parentUnit = current.Data; } } else { //jamais rencontré test.Data.f = f; test.Data.h = h; test.Data.g = g; test.Data.parentUnit = current.Data; open.Add(test); } } closed.Add (current); if(open.Count == 0) { Debug.Log("nothingfound"); //nothing more to test no path found, stay to from; List<GridUnit> r = new List<GridUnit>(); r.Add(from.Data); return r; } //sort open from small to biggest travel cost open.Sort(delegate(Node<GridUnit> x, Node<GridUnit> y) { return (int)(x.Data.f-y.Data.f); }); //get the smallest travel cost node; Node<GridUnit> smallest = open[0]; current = smallest; open.RemoveAt(0); } //build the path going backward; List<GridUnit> ret = new List<GridUnit>(); if(penul != null) { ret.Insert(0,to.Data); } GridUnit cur = goal.Data; ret.Insert(0,cur); do{ cur = cur.parentUnit; ret.Insert(0,cur); } while(cur != from.Data); return ret; You see at the start of the foreach i constrict the A* like i said. If you have any insight it would be cool. Thanks

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• Create a thread in xna Update method to find path?

  - by Dan

  I am trying to create a separate thread for my enemy's A* pathfinder which will give me a list of points to get to the player. I have placed the thread in the update method of my enemy. However this seems to cause jittering in the game every-time the thread is called. I have tried calling just the method and this works fine. Is there any way I can sort this out so that I can have the pathfinder on its own thread? Do I need to remove the thread start from the update and start it in the constructor? Is there any way this can work. Here is the code at the moment: bool running = false; bool threadstarted; System.Threading.Thread thread; public void update() { if (running == false && threadstarted == false) { thread = new System.Threading.Thread(PathThread); //thread.Priority = System.Threading.ThreadPriority.Lowest; thread.IsBackground = true; thread.Start(startandendobj); //PathThread(startandendobj); threadstarted = true; } } public void PathThread(object Startandend) { object[] Startandendarray = (object[])Startandend; Point startpoint = (Point)Startandendarray[0]; Point endpoint = (Point)Startandendarray[1]; bool runnable = true; // Path find from 255, 255 to 0,0 on the map foreach(Tile tile in Map) { if(tile.Color == Color.Red) { if (tile.Position.Contains(endpoint)) { runnable = false; } } } if(runnable == true) { running = true; Pathfinder p = new Pathfinder(Map); pathway = p.FindPath(startpoint, endpoint); running = false; threadstarted = false; } }

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• How do I make A* check all diagonal and orthogonal directions?

  - by Munezane

  I'm making a turn-based tactical game and I'm trying to implement the A* algorithm. I've been following a tutorial and got to this point, but my characters can't move diagonally up and left. Can anyone help me with this? The return x and y are int pointers which the characters are using to move towards the target. void level::aStar(int startx, int starty, int targetx, int targety, int* returnx, int* returny) { aStarGridSquare* currentSquare = new aStarGridSquare(); aStarGridSquare* startSquare = new aStarGridSquare(); aStarGridSquare* targetSquare = new aStarGridSquare(); aStarGridSquare* adjacentSquare = new aStarGridSquare(); aStarOpenList.clear(); for(unsigned int i=0; i<aStarGridSquareList.size(); i++) { aStarGridSquareList[i]->open=false; aStarGridSquareList[i]->closed=false; } startSquare=getaStarGridSquare(startx, starty); targetSquare=getaStarGridSquare(targetx, targety); if(startSquare==targetSquare) { *returnx=startx; *returny=starty; return; } startSquare->CostFromStart=0; startSquare->CostToTraverse=0; startSquare->parent = NULL; currentSquare=startSquare; aStarOpenList.push_back(currentSquare); while(currentSquare!=targetSquare && aStarOpenList.size()>0) { //unsigned int totalCostEstimate=aStarOpenList[0]->TotalCostEstimate; //currentSquare=aStarOpenList[0]; for(unsigned int i=0; i<aStarOpenList.size(); i++) { if(aStarOpenList.size()>1) { for(unsigned int j=1; j<aStarOpenList.size()-1; j++) { if(aStarOpenList[i]->TotalCostEstimate<aStarOpenList[j]->TotalCostEstimate) { currentSquare=aStarOpenList[i]; } else { currentSquare=aStarOpenList[j]; } } } else { currentSquare = aStarOpenList[i]; } } currentSquare->closed=true; currentSquare->open=false; for(unsigned int i=0; i<aStarOpenList.size(); i++) { if(aStarOpenList[i]==currentSquare) { aStarOpenList.erase(aStarOpenList.begin()+i); } } for(unsigned int i = currentSquare->blocky - 32; i <= currentSquare->blocky + 32; i+=32) { for(unsigned int j = currentSquare->blockx - 32; j<= currentSquare->blockx + 32; j+=32) { adjacentSquare=getaStarGridSquare(j/32, i/32); if(adjacentSquare!=NULL) { if(adjacentSquare->blocked==false && adjacentSquare->closed==false) { if(adjacentSquare->open==false) { adjacentSquare->parent=currentSquare; if(currentSquare->parent!=NULL) { currentSquare->CostFromStart = currentSquare->parent->CostFromStart + currentSquare->CostToTraverse + startSquare->CostFromStart; } else { currentSquare->CostFromStart=0; } adjacentSquare->CostFromStart =currentSquare->CostFromStart + adjacentSquare->CostToTraverse;// adjacentSquare->parent->CostFromStart + adjacentSquare->CostToTraverse; //currentSquare->CostToEndEstimate = abs(currentSquare->blockx - targetSquare->blockx) + abs(currentSquare->blocky - targetSquare->blocky); //currentSquare->TotalCostEstimate = currentSquare->CostFromStart + currentSquare->CostToEndEstimate; adjacentSquare->open = true; adjacentSquare->CostToEndEstimate=abs(adjacentSquare->blockx- targetSquare->blockx) + abs(adjacentSquare->blocky-targetSquare->blocky); adjacentSquare->TotalCostEstimate = adjacentSquare->CostFromStart+adjacentSquare->CostToEndEstimate; //adjacentSquare->open=true;*/ aStarOpenList.push_back(adjacentSquare); } else { if(adjacentSquare->parent->CostFromStart > currentSquare->CostFromStart) { adjacentSquare->parent=currentSquare; if(currentSquare->parent!=NULL) { currentSquare->CostFromStart = currentSquare->parent->CostFromStart + currentSquare->CostToTraverse + startSquare->CostFromStart; } else { currentSquare->CostFromStart=0; } adjacentSquare->CostFromStart =currentSquare->CostFromStart + adjacentSquare->CostToTraverse;// adjacentSquare->parent->CostFromStart + adjacentSquare->CostToTraverse; //currentSquare->CostToEndEstimate = abs(currentSquare->blockx - targetSquare->blockx) + abs(currentSquare->blocky - targetSquare->blocky); //currentSquare->TotalCostEstimate = currentSquare->CostFromStart + currentSquare->CostToEndEstimate; adjacentSquare->CostFromStart = adjacentSquare->parent->CostFromStart + adjacentSquare->CostToTraverse; adjacentSquare->CostToEndEstimate=abs(adjacentSquare->blockx - targetSquare->blockx) + abs(adjacentSquare->blocky - targetSquare->blocky); adjacentSquare->TotalCostEstimate = adjacentSquare->CostFromStart+adjacentSquare->CostToEndEstimate; } } } } } } } if(aStarOpenList.size()==0)//if empty { *returnx =startx; *returny =starty; return; } else { for(unsigned int i=0; i< aStarOpenList.size(); i++) { if(currentSquare->parent==NULL) { //int tempX = targetSquare->blockx; //int tempY = targetSquare->blocky; *returnx=targetSquare->blockx; *returny=targetSquare->blocky; break; } else { currentSquare=currentSquare->parent; } } } }

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• Pathfinding with MicroPather : costs calculations with sectors and portals

  - by Adan

  Hello, I'm considering using micropather to help me with pathfinding. I'm not using a discrete map : I'm working in 2d with sectors and portales. However, I'm just wondering what is the best way to compute costs with this library in this context. Just to be more clear about geometrical shapes I'm using : sectors are basically convex polygons, and portals are segments that lies on sector's edge. Micropather exposes a pure virtual Graph class that you must inherate and overrides 3 functions. I understand how pathfinding works, so there's no problem in overriding those functions. Right now, my implementation give me results, i.e I'm able to find a path in my map, but I'm not sure I'm using an optimal solution. For the AdjacentCost method : I just take the distance between sector's centers as the cost. I think a better solution should be to use the portal between the two sectors, compute its center, and then the cost should be : distance( sector A center, portal center ) + distance ( sector B center, portal center ). I'm pretty sure the approximation I'm using with just sector's center is enough for most cases, but maybe with thin and long sectors that are perpendicular, this approximation could mislead the A* algorithm. For the LeastCostEstimate method : I just take the midpoint of the two sectors. So, as you understand, I'm always working with sectors' centers, and it's working fine. And I'm pretty sure there's a better way to work. Any suggestions or feedbacks? Thanks in advance!

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• How can I plot a radius of all reachable points with pathfinding for a Mob?

  - by PugWrath

  I am designing a tactical turn based game. The maps are 2d, but do have varying level-layers and blocking objects/terrain. I'm looking for an algorithm for pathfinding which will allow me to show an opaque shape representing all of the possible max-distance pixels that a mob can move to, knowing the mob's max pixel distance. Any thoughts on this, or do I just need to write a good pathfinding algorithm and use it to find the cutoff points for any direction in which an obstacle exists?

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• Dynamic navigation mesh changes

  - by Nairou

  I'm currently trying to convert from grids to navigation meshes for pathfinding, since grids are either too coarse for accurate navigation, or too fine to be useful for object tracking. While my map is fairly static, and the navigation mesh could be created in advance, this is somewhat of a tower defense game, where objects can be placed to block paths, so I need a way to recalculate portions of the navigation mesh to allow pathing around them. Is there any existing documentation on good ways to do this? I'm still very new to navigation meshes, so the prospect of modifying them to cut or fill holes sounds daunting.

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• A* how make natural look path?

  - by user11177

  I've been reading this: http://theory.stanford.edu/~amitp/GameProgramming/Heuristics.html But there are some things I don't understand, for example the article says to use something like this for pathfinding with diagonal movement: function heuristic(node) = dx = abs(node.x - goal.x) dy = abs(node.y - goal.y) return D * max(dx, dy) I don't know how do set D to get a natural looking path like in the article, I set D to the lowest cost between adjacent squares like it said, and I don't know what they meant by the stuff about the heuristic should be 4*D, that does not seem to change any thing. This is my heuristic function and move function: def heuristic(self, node, goal): D = 10 dx = abs(node.x - goal.x) dy = abs(node.y - goal.y) return D * max(dx, dy) def move_cost(self, current, node): cross = abs(current.x - node.x) == 1 and abs(current.y - node.y) == 1 return 19 if cross else 10 Result: The smooth sailing path we want to happen: The rest of my code: http://pastebin.com/TL2cEkeX

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• Combining pathfinding with global AI objectives

  - by V_Programmer

  I'm making a turn-based strategy game using Java and LibGDX. Now I want to code the AI. I haven't written the AI code yet. I've simply designed it. The AI will have two components, one focused in tactics and resource management (create troops, determine who have strategical advantage, detect important objectives, etc) and a individual component, focused in assign the work to each unit, examine its possibilites and move the unit. Now I'm facing an important problem. The map where the action take place is a grid-based map. Each terrain has different movement cost. I read about pathfinding and I think A* is a very good option to determine a good route between two points. However, imagine I have an unit with movement = 5 (i.e, it can move 5 tiles of movement cost = 1). My tactical AI has found an objective at a distance d = 20 tiles (Manhattan distance) from my unit. My problem is the following: the unit won't be able to reach the objective in one turn. So the AI will have to store a list of position and execute them in various turns. I don't know how to solve this. PS. In my unit code, I have a list called "selectionMarks" which stores all the possible places where the unit can go in this turn. This places are calculed recursively using a "getSelectionMarks" function. Any help is appreciated :D

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• What's the best way to move cars along roads

  - by David Thielen

  I am implementing car movement game (sort-of like Locomotion). So 60 times a second I have to advance the movement of each car. The problem is I have to look ahead to see if there is a slower car, stop sign, or red light ahead. And then slow down appropiately. I also want to have the cars take time to go from stopped to full speed and again to slow down. I'm not implementing full-blown physics, but just a tick by tick speed up/slow down as that provides most of the realism to match what people expect to see. The best I've come up with is to walk out the full distance the car would travel of it was slowing to a stop and see if anywhere along that path it needed to slow down or stop. And then move it forward appropiately. I am moving the cars 60 times a second so I need this to be fast. And walking out that whole path each tick strikes me as processor intensive. What's the best way to do this?

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• Low CPU/Memory/Memory-bandwith Pathfinding (maybe like in Warcraft 1)

  - by Valmond

  Dijkstra and A* are all nice and popular but what kind of algorithm was used in Warcraft 1 for pathfinding? I remember that the enemy could get trapped in bowl-like caverns which means there were (most probably) no full-path calculations from "start to end". If I recall correctly, the algorithm could be something like this: A) Move towards enemy until success or hitting a wall B) If blocked by a wall, follow the wall until you can move towards the enemy without being blocked and then do A) But I'd like to know, if someone knows :-) [edit] As explained to Byte56, I'm searching for a low cpu/mem/mem-bandwidth algo and wanted to know if Warcraft had some special secrets to deliver (never seen that kind of pathfinding elsewhere), I hope that that is more concordant with the stackexchange rules.

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• How to make natural-looking paths with A* on a grid?

  - by user11177

  I've been reading this: http://theory.stanford.edu/~amitp/GameProgramming/Heuristics.html But there are some things I don't understand, for example the article says to use something like this for pathfinding with diagonal movement: function heuristic(node) = dx = abs(node.x - goal.x) dy = abs(node.y - goal.y) return D * max(dx, dy) I don't know how do set D to get a natural looking path like in the article, I set D to the lowest cost between adjacent squares like it said, and I don't know what they meant by the stuff about the heuristic should be 4*D, that does not seem to change any thing. This is my heuristic function and move function: def heuristic(self, node, goal): D = 10 dx = abs(node.x - goal.x) dy = abs(node.y - goal.y) return D * max(dx, dy) def move_cost(self, current, node): cross = abs(current.x - node.x) == 1 and abs(current.y - node.y) == 1 return 19 if cross else 10 Result: The smooth sailing path we want to happen: The rest of my code: http://pastebin.com/TL2cEkeX

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• 3D RTS pathfinding

  - by xcrypt

  I understand the A* algorithm, but I have some trouble doing it in 3D to suit the needs of my RTS Basically, in the game I'm making, there will be agents with different sizes of OBB collision boxes. I can use steering behaviours for avoiding other agents, so I don't need complete dynamic pathfinding. However, there is a problem because different agents have different collision geometry, and structures can be placed in almost any place. This means that there might be a gap between two structures where some agents can go through and some can't. A solution I have found to this problem is to do a sweep of the collision geometry of the agent from start node of the edge the pf algorithm is currently testing, to the end node of that edge. But this is probably a bit overkill since every edge the algorithm tests would also have to create and test with a collision geometry sweep. What are some reasonable approaches to this problem? I should mention that I'd prefer not to use navmeshes, I prefer waypoints because my entire system is based on it atm.

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• Having trouble with pathfinding

  - by user2144536

  I'm trying to implement pathfinding in a game I'm programming using this method. I'm implementing it with recursion but some of the values after the immediate circle of tiles around the player are way off. For some reason I cannot find the problem with it. This is a screen cap of the problem: The pathfinding values are displayed in the center of every tile. Clipped blocks are displayed with the value of 'c' because the values were too high and were covering up the next value. The red circle is the first value that is incorrect. The code below is the recursive method. //tileX is the coordinates of the current tile, val is the current pathfinding value, used[][] is a boolean //array to keep track of which tiles' values have already been assigned public void pathFind(int tileX, int tileY, int val, boolean[][] used) { //increment pathfinding value int curVal = val + 1; //set current tile to true if it hasn't been already used[tileX][tileY] = true; //booleans to know which tiles the recursive call needs to be used on boolean topLeftUsed = false, topUsed = false, topRightUsed = false, leftUsed = false, rightUsed = false, botomLeftUsed = false, botomUsed = false, botomRightUsed = false; //set value of top left tile if necessary if(tileX - 1 >= 0 && tileY - 1 >= 0) { //isClipped(int x, int y) returns true if the coordinates givin are in a tile that can't be walked through (IE walls) //occupied[][] is an array that keeps track of which tiles have an enemy in them // //if the tile is not clipped and not occupied set the pathfinding value if(isClipped((tileX - 1) * 50 + 25, (tileY - 1) * 50 + 25) == false && occupied[tileX - 1][tileY - 1] == false && !(used[tileX - 1][tileY - 1])) { pathFindingValues[tileX - 1][tileY - 1] = curVal; topLeftUsed = true; used[tileX - 1][tileY - 1] = true; } //if it is occupied set it to an arbitrary high number so enemies find alternate routes if the best is clogged if(occupied[tileX - 1][tileY - 1] == true) pathFindingValues[tileX - 1][tileY - 1] = 1000000000; //if it is clipped set it to an arbitrary higher number so enemies don't travel through walls if(isClipped((tileX - 1) * 50 + 25, (tileY - 1) * 50 + 25) == true) pathFindingValues[tileX - 1][tileY - 1] = 2000000000; } //top middle if(tileY - 1 >= 0 ) { if(isClipped(tileX * 50 + 25, (tileY - 1) * 50 + 25) == false && occupied[tileX][tileY - 1] == false && !(used[tileX][tileY - 1])) { pathFindingValues[tileX][tileY - 1] = curVal; topUsed = true; used[tileX][tileY - 1] = true; } if(occupied[tileX][tileY - 1] == true) pathFindingValues[tileX][tileY - 1] = 1000000000; if(isClipped(tileX * 50 + 25, (tileY - 1) * 50 + 25) == true) pathFindingValues[tileX][tileY - 1] = 2000000000; } //top right if(tileX + 1 <= used.length && tileY - 1 >= 0) { if(isClipped((tileX + 1) * 50 + 25, (tileY - 1) * 50 + 25) == false && occupied[tileX + 1][tileY - 1] == false && !(used[tileX + 1][tileY - 1])) { pathFindingValues[tileX + 1][tileY - 1] = curVal; topRightUsed = true; used[tileX + 1][tileY - 1] = true; } if(occupied[tileX + 1][tileY - 1] == true) pathFindingValues[tileX + 1][tileY - 1] = 1000000000; if(isClipped((tileX + 1) * 50 + 25, (tileY - 1) * 50 + 25) == true) pathFindingValues[tileX + 1][tileY - 1] = 2000000000; } //left if(tileX - 1 >= 0) { if(isClipped((tileX - 1) * 50 + 25, (tileY) * 50 + 25) == false && occupied[tileX - 1][tileY] == false && !(used[tileX - 1][tileY])) { pathFindingValues[tileX - 1][tileY] = curVal; leftUsed = true; used[tileX - 1][tileY] = true; } if(occupied[tileX - 1][tileY] == true) pathFindingValues[tileX - 1][tileY] = 1000000000; if(isClipped((tileX - 1) * 50 + 25, (tileY) * 50 + 25) == true) pathFindingValues[tileX - 1][tileY] = 2000000000; } //right if(tileX + 1 <= used.length) { if(isClipped((tileX + 1) * 50 + 25, (tileY) * 50 + 25) == false && occupied[tileX + 1][tileY] == false && !(used[tileX + 1][tileY])) { pathFindingValues[tileX + 1][tileY] = curVal; rightUsed = true; used[tileX + 1][tileY] = true; } if(occupied[tileX + 1][tileY] == true) pathFindingValues[tileX + 1][tileY] = 1000000000; if(isClipped((tileX + 1) * 50 + 25, (tileY) * 50 + 25) == true) pathFindingValues[tileX + 1][tileY] = 2000000000; } //botom left if(tileX - 1 >= 0 && tileY + 1 <= used[0].length) { if(isClipped((tileX - 1) * 50 + 25, (tileY + 1) * 50 + 25) == false && occupied[tileX - 1][tileY + 1] == false && !(used[tileX - 1][tileY + 1])) { pathFindingValues[tileX - 1][tileY + 1] = curVal; botomLeftUsed = true; used[tileX - 1][tileY + 1] = true; } if(occupied[tileX - 1][tileY + 1] == true) pathFindingValues[tileX - 1][tileY + 1] = 1000000000; if(isClipped((tileX - 1) * 50 + 25, (tileY + 1) * 50 + 25) == true) pathFindingValues[tileX - 1][tileY + 1] = 2000000000; } //botom middle if(tileY + 1 <= used[0].length) { if(isClipped((tileX) * 50 + 25, (tileY + 1) * 50 + 25) == false && occupied[tileX][tileY + 1] == false && !(used[tileX][tileY + 1])) { pathFindingValues[tileX][tileY + 1] = curVal; botomUsed = true; used[tileX][tileY + 1] = true; } if(occupied[tileX][tileY + 1] == true) pathFindingValues[tileX][tileY + 1] = 1000000000; if(isClipped((tileX) * 50 + 25, (tileY + 1) * 50 + 25) == true) pathFindingValues[tileX][tileY + 1] = 2000000000; } //botom right if(tileX + 1 <= used.length && tileY + 1 <= used[0].length) { if(isClipped((tileX + 1) * 50 + 25, (tileY + 1) * 50 + 25) == false && occupied[tileX + 1][tileY + 1] == false && !(used[tileX + 1][tileY + 1])) { pathFindingValues[tileX + 1][tileY + 1] = curVal; botomRightUsed = true; used[tileX + 1][tileY + 1] = true; } if(occupied[tileX + 1][tileY + 1] == true) pathFindingValues[tileX + 1][tileY + 1] = 1000000000; if(isClipped((tileX + 1) * 50 + 25, (tileY + 1) * 50 + 25) == true) pathFindingValues[tileX + 1][tileY + 1] = 2000000000; } //call the method on the tiles that need it if(tileX - 1 >= 0 && tileY - 1 >= 0 && topLeftUsed) pathFind(tileX - 1, tileY - 1, curVal, used); if(tileY - 1 >= 0 && topUsed) pathFind(tileX , tileY - 1, curVal, used); if(tileX + 1 <= used.length && tileY - 1 >= 0 && topRightUsed) pathFind(tileX + 1, tileY - 1, curVal, used); if(tileX - 1 >= 0 && leftUsed) pathFind(tileX - 1, tileY, curVal, used); if(tileX + 1 <= used.length && rightUsed) pathFind(tileX + 1, tileY, curVal, used); if(tileX - 1 >= 0 && tileY + 1 <= used[0].length && botomLeftUsed) pathFind(tileX - 1, tileY + 1, curVal, used); if(tileY + 1 <= used[0].length && botomUsed) pathFind(tileX, tileY + 1, curVal, used); if(tileX + 1 <= used.length && tileY + 1 <= used[0].length && botomRightUsed) pathFind(tileX + 1, tileY + 1, curVal, used); }

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• Prevent collisions between mobs/npcs/units piloted by computer AI : How to avoid mobile obstacles?

  - by Arthur Wulf White

  Lets says we have character a starting at point A and character b starting at point B. character a is headed to point B and character b is headed to point A. There are several simple ways to find the path(I will be using Dijkstra). The question is, how do I take preventative action in the code to stop the two from colliding with one another? case2: Characters a and b start from the same point in different times. Character b starts later and is the faster of the two. How do I make character b walk around character a without going through it? case3:Lets say we have m such characters in each side and there is sufficient room to pass through without the characters overlapping with one another. How do I stop the two groups of characters from "walking on top of one another" and allow them pass around one another in a natural organic way. A correct answer would be any algorithm, that given the path to the destination and a list of mobile objects that block the path, finds an alternative path or stops without stopping all units when there is sufficient room to traverse.

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• Unit turning in navmesh-based pathfinding

  - by Haddayn

  I'm working on an RTS game, and I'm using navmeshes for unit pathfinding. I do know how to find a general path within a navmesh, but how do you determine if the unit have enough space to turn? I have units of different shapes (mostly rectangles with different dimensions), and with different turn radii. Additionally some of units can turn in place, and some can move in reverse. So, how to find a path which unit can follow, considering that it can not rotate easily?

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• Constrained A* problem

  - by Ragekit

  I've got a little problem with an A* algorithm that I need to Constrained a little bit. Basically : I use an A* to find the shortest path between 2 randomly placed room in 3D space, and then build a corridor between them. The problem I found is that sometimes it makes chimney like corridors that are not ideal, so I constrict the A* so that if the last movement was up or down, you go sideways. Everything is fine, but in some corner cases, it fails to find a path (when there is obviously one). Like here between the blue and red dot : (i'm in unity btw, but i don't think it matters) Here is the code of the actual A* (a bit long, and some redundency) while(current != goal) { //add stair up / stair down foreach(Node<GridUnit> test in current.Neighbors) { if(!test.Data.empty && test != goal) continue; //bug at arrival; if(test == goal && penul !=null) { Vector3 currentDiff = current.Data.bounds.center - test.Data.bounds.center; if(!Mathf.Approximately(currentDiff.y,0)) { //wanna drop on the last if(!coplanar(test.Data.bounds.center,current.Data.bounds.center,current.Data.parentUnit.bounds.center,to.Data.bounds.center)) { continue; } else { if(Mathf.Approximately(to.Data.bounds.center.x, current.Data.parentUnit.bounds.center.x) && Mathf.Approximately(to.Data.bounds.center.z, current.Data.parentUnit.bounds.center.z)) { continue; } } } } if(current.Data.parentUnit != null) { Vector3 previousDiff = current.Data.parentUnit.bounds.center - current.Data.bounds.center; Vector3 currentDiff = current.Data.bounds.center - test.Data.bounds.center; if(!Mathf.Approximately(previousDiff.y,0)) { if(!Mathf.Approximately(currentDiff.y,0)) { //you wanna drop now : continue; } if(current.Data.parentUnit.parentUnit != null) { if(!coplanar(test.Data.bounds.center,current.Data.bounds.center,current.Data.parentUnit.bounds.center,current.Data.parentUnit.parentUnit.bounds.center)) { continue; }else { if(Mathf.Approximately(test.Data.bounds.center.x, current.Data.parentUnit.parentUnit.bounds.center.x) && Mathf.Approximately(test.Data.bounds.center.z, current.Data.parentUnit.parentUnit.bounds.center.z)) { continue; } } } } } g = current.Data.g + HEURISTIC(current.Data,test.Data); h = HEURISTIC(test.Data,goal.Data); f = g + h; if(open.Contains(test) || closed.Contains(test)) { if(test.Data.f > f) { //found a shorter path going passing through that point test.Data.f = f; test.Data.g = g; test.Data.h = h; test.Data.parentUnit = current.Data; } } else { //jamais rencontré test.Data.f = f; test.Data.h = h; test.Data.g = g; test.Data.parentUnit = current.Data; open.Add(test); } } closed.Add (current); if(open.Count == 0) { Debug.Log("nothingfound"); //nothing more to test no path found, stay to from; List<GridUnit> r = new List<GridUnit>(); r.Add(from.Data); return r; } //sort open from small to biggest travel cost open.Sort(delegate(Node<GridUnit> x, Node<GridUnit> y) { return (int)(x.Data.f-y.Data.f); }); //get the smallest travel cost node; Node<GridUnit> smallest = open[0]; current = smallest; open.RemoveAt(0); } //build the path going backward; List<GridUnit> ret = new List<GridUnit>(); if(penul != null) { ret.Insert(0,to.Data); } GridUnit cur = goal.Data; ret.Insert(0,cur); do{ cur = cur.parentUnit; ret.Insert(0,cur); } while(cur != from.Data); return ret; You see at the start of the foreach i constrict the A* like i said. If you have any insight it would be cool. Thanks

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• Pathfinding in Warcraft 1

  - by Valmond

  Dijkstra and A* are all nice and popular but what kind of algorithm was used in Warcraft 1 for pathfinding? I remember that the enemy could get trapped in bowl-like caverns which means there were (most probably) no full-path calculations from "start to end". If I recall correctly, the algorithm could be something like this: A) Move towards enemy until success or hitting a wall B) If blocked by a wall, follow the wall until you can move towards the enemy without being blocked and then do A) But I'd like to know, if someone knows :-)

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• Is my implementation of A* wrong?

  - by Bloodyaugust

  I've implemented the A* algorithm in my program. However, it would seem to be functioning incorrectly at times. Below is a screenshot of one such time. The obviously shorter line is to go immediately right at the second to last row. Instead, they move down, around the tower, and continue to their destination (bottom right from top left). Below is my actual code implementation: nodeMap.prototype.findPath = function(p1, p2) { var openList = []; var closedList = []; var nodes = this.nodes; for (var i = 0; i < nodes.length; i++) { //reset heuristics and parents for nodes var curNode = nodes[i]; curNode.f = 0; curNode.g = 0; curNode.h = 0; curNode.parent = null; if (curNode.pathable === false) { closedList.push(curNode); } } openList.push(this.getNode(p1)); while(openList.length > 0) { // Grab the lowest f(x) to process next var lowInd = 0; for(i=0; i<openList.length; i++) { if(openList[i].f < openList[lowInd].f) { lowInd = i; } } var currentNode = openList[lowInd]; if (currentNode === this.getNode(p2)) { var curr = currentNode; var ret = []; while(curr.parent) { ret.push(curr); curr = curr.parent; } return ret.reverse(); } closedList.push(currentNode); for (i = 0; i < openList.length; i++) { //remove currentNode from openList if (openList[i] === currentNode) { openList.splice(i, 1); break; } } for (i = 0; i < currentNode.neighbors.length; i++) { if(closedList.indexOf(currentNode.neighbors[i]) !== -1 ) { continue; } if (currentNode.neighbors[i].isPathable === false) { closedList.push(currentNode.neighbors[i]); continue; } var gScore = currentNode.g + 1; // 1 is the distance from a node to it's neighbor var gScoreIsBest = false; if (openList.indexOf(currentNode.neighbors[i]) === -1) { //save g, h, and f then save the current parent gScoreIsBest = true; currentNode.neighbors[i].h = currentNode.neighbors[i].heuristic(this.getNode(p2)); openList.push(currentNode.neighbors[i]); } else if (gScore < currentNode.neighbors[i].g) { //current g better than previous g gScoreIsBest = true; } if (gScoreIsBest) { currentNode.neighbors[i].parent = currentNode; currentNode.neighbors[i].g = gScore; currentNode.neighbors[i].f = currentNode.neighbors[i].g + currentNode.neighbors[i].h; } } } return false; } Towers block pathability. Is there perhaps something I am missing here, or does A* not always find the shortest path in a situation such as this? Thanks in advance for any help.

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• A* PathFinding Poor Performance

  - by RedShft

  After debugging for a few hours, the algorithm seems to be working. Right now to check if it works i'm checking the end node position to the currentNode position when the while loop quits. So far the values look correct. The problem is, the farther I get from the NPC, who is current stationary, the worse the performance gets. It gets to a point where the game is unplayable less than 10 fps. My current PathGraph is 2500 nodes, which I believe is pretty small, right? Any ideas on how to improve performance? struct Node { bool walkable; //Whether this node is blocked or open vect2 position; //The tile's position on the map in pixels int xIndex, yIndex; //The index values of the tile in the array Node*[4] connections; //An array of pointers to nodes this current node connects to Node* parent; int gScore; int hScore; int fScore; } class AStar { private: SList!Node openList; SList!Node closedList; //Node*[4] connections; //The connections of the current node; Node currentNode; //The current node being processed Node[] Path; //The path found; const int connectionCost = 10; Node start, end; ////////////////////////////////////////////////////////// void AddToList(ref SList!Node list, ref Node node ) { list.insert( node ); } void RemoveFrom(ref SList!Node list, ref Node node ) { foreach( elem; list ) { if( node.xIndex == elem.xIndex && node.yIndex == elem.yIndex ) { auto a = find( list[] , elem ); list.linearRemove( take(a, 1 ) ); } } } bool IsInList( SList!Node list, ref Node node ) { foreach( elem; list ) { if( node.xIndex == elem.xIndex && node.yIndex == elem.yIndex ) return true; } return false; } void ClearList( SList!Node list ) { list.clear; } void SetParentNode( ref Node parent, ref Node child ) { child.parent = &parent; } void SetStartAndEndNode( vect2 vStart, vect2 vEnd, Node[] PathGraph ) { int startXIndex, startYIndex; int endXIndex, endYIndex; startXIndex = cast(int)( vStart.x / 32 ); startYIndex = cast(int)( vStart.y / 32 ); endXIndex = cast(int)( vEnd.x / 32 ); endYIndex = cast(int)( vEnd.y / 32 ); foreach( node; PathGraph ) { if( node.xIndex == startXIndex && node.yIndex == startYIndex ) { start = node; } if( node.xIndex == endXIndex && node.yIndex == endYIndex ) { end = node; } } } void SetStartScores( ref Node start ) { start.gScore = 0; start.hScore = CalculateHScore( start, end ); start.fScore = CalculateFScore( start ); } Node GetLowestFScore() { Node lowest; lowest.fScore = 10000; foreach( elem; openList ) { if( elem.fScore < lowest.fScore ) lowest = elem; } return lowest; } //This function current sets the program into an infinite loop //I still need to debug to figure out why the parent nodes aren't correct void GeneratePath() { while( currentNode.position != start.position ) { Path ~= currentNode; currentNode = *currentNode.parent; } } void ReversePath() { Node[] temp; for(int i = Path.length - 1; i >= 0; i-- ) { temp ~= Path[i]; } Path = temp.dup; } public: //@FIXME It seems to find the path, but now performance is terrible void FindPath( vect2 vStart, vect2 vEnd, Node[] PathGraph ) { openList.clear; closedList.clear; SetStartAndEndNode( vStart, vEnd, PathGraph ); SetStartScores( start ); AddToList( openList, start ); while( currentNode.position != end.position ) { currentNode = GetLowestFScore(); if( currentNode.position == end.position ) break; else { RemoveFrom( openList, currentNode ); AddToList( closedList, currentNode ); for( int i = 0; i < currentNode.connections.length; i++ ) { if( currentNode.connections[i] is null ) continue; else { if( IsInList( closedList, *currentNode.connections[i] ) && currentNode.gScore < currentNode.connections[i].gScore ) { currentNode.connections[i].gScore = currentNode.gScore + connectionCost; currentNode.connections[i].hScore = abs( currentNode.connections[i].xIndex - end.xIndex ) + abs( currentNode.connections[i].yIndex - end.yIndex ); currentNode.connections[i].fScore = currentNode.connections[i].gScore + currentNode.connections[i].hScore; currentNode.connections[i].parent = &currentNode; } else if( IsInList( openList, *currentNode.connections[i] ) && currentNode.gScore < currentNode.connections[i].gScore ) { currentNode.connections[i].gScore = currentNode.gScore + connectionCost; currentNode.connections[i].hScore = abs( currentNode.connections[i].xIndex - end.xIndex ) + abs( currentNode.connections[i].yIndex - end.yIndex ); currentNode.connections[i].fScore = currentNode.connections[i].gScore + currentNode.connections[i].hScore; currentNode.connections[i].parent = &currentNode; } else { currentNode.connections[i].gScore = currentNode.gScore + connectionCost; currentNode.connections[i].hScore = abs( currentNode.connections[i].xIndex - end.xIndex ) + abs( currentNode.connections[i].yIndex - end.yIndex ); currentNode.connections[i].fScore = currentNode.connections[i].gScore + currentNode.connections[i].hScore; currentNode.connections[i].parent = &currentNode; AddToList( openList, *currentNode.connections[i] ); } } } } } writeln( "Current Node Position: ", currentNode.position ); writeln( "End Node Position: ", end.position ); if( currentNode.position == end.position ) { writeln( "Current Node Parent: ", currentNode.parent ); //GeneratePath(); //ReversePath(); } } Node[] GetPath() { return Path; } } This is my first attempt at A* so any help would be greatly appreciated.

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• A* algorithm very slow

  - by Amaranth

  I have an programming a RTS game (I use XNA with C#). The pathfinding is working fine, except that when it has a lot of node to search in, there is a lag period of one or two seconds, it happens mainly when there is no path to the target destination, since it that situation there is more nodes to explore. I have the same problem when the path is shorter but selected more than 3 units (can't take the same path since the selected units can be in different part of the map). private List<NodeInfo> FindPath(Unit u, NodeInfo start, NodeInfo end) { Map map = GameInfo.GetInstance().GameMap; _nearestToTarget = start; start.MoveCost = 0; Vector2 endPosition = map.getTileByPos(end.X, end.Y).Position; //getTileByPos simply gets the tile in a 2D array with the X and Y indexes start.EstimatedRemainingCost = (int)(endPosition - map.getTileByPos(start.X, start.Y).Position).Length(); start.Parent = null; List<NodeInfo> openedNodes = new List<NodeInfo>(); ; List<NodeInfo> closedNodes = new List<NodeInfo>(); Point[] movements = GetMovements(u.UnitType); openedNodes.Add(start); while (!closedNodes.Contains(end) && openedNodes.Count > 0) { //Loop in nodes to find lowest cost NodeInfo currentNode = FindLowestCostOpenedNode(openedNodes); openedNodes.Remove(currentNode); closedNodes.Add(currentNode); Vector2 previousMouvement; if (currentNode.Parent == null) { previousMouvement = ConvertRotationToDirectionVector(u.Rotation); } else { previousMouvement = map.getTileByPos(currentNode.X, currentNode.Y).Position - map.getTileByPos(currentNode.Parent.X, currentNode.Parent.Y).Position; previousMouvement.Normalize(); } //For each neighbor foreach (Point movement in movements) { Point exploredGridPos = new Point(currentNode.X + movement.X, currentNode.Y + movement.Y); //Checks if valid move and checks if not if closed nodes list if (ValidNavigableNode(u.UnitType, new Point(currentNode.X, currentNode.Y), exploredGridPos) && !closedNodes.Contains(_gridMap[exploredGridPos.Y, exploredGridPos.X])) { NodeInfo exploredNode = _gridMap[exploredGridPos.Y, exploredGridPos.X]; Tile.TileType exploredTerrain = map.getTileByPos(exploredGridPos.X, exploredGridPos.Y).TerrainType; if(openedNodes.Contains(exploredNode)) { int newCost = currentNode.MoveCost + GetMoveCost(previousMouvement, movement, exploredTerrain); if (newCost < exploredNode.MoveCost) { exploredNode.Parent = currentNode; exploredNode.MoveCost = newCost; //Find nearest tile to the target (in case doesn't find path to target) //Only compares the node to the current nearest FindNearest(exploredNode); } } else { exploredNode.Parent = currentNode; exploredNode.MoveCost = currentNode.MoveCost + GetMoveCost(previousMouvement, movement, exploredTerrain); Vector2 exploredNodeWorldPos = map.getTileByPos(exploredGridPos.X, exploredGridPos.Y).Position; exploredNode.EstimatedRemainingCost = (int)(endPosition - exploredNodeWorldPos).Length(); //Find nearest tile to the target (in case doesn't find path to target) //Only compares the node to the current nearest FindNearest(exploredNode); openedNodes.Add(exploredNode); } } } } return closedNodes; } After that, I simply check if the end node is contained in the returned nodes. If so, I add the end node and each parent until I reach the start. If not, I add the nearestToTarget and each parent until I reach the start. I added a condition before calling FindPath so that only one unit can call a find path each frame (60 frame per second), but it makes no difference. I thought maybe I could solve this by allowing the find path to run in background while the game continues to run correctly, even if it takes a few frame (it is currently sequential sonce it is called in the update() of the unit if there's a target location but no path), but I don't really know how... I also though about sorting my opened nodes list by cost so I don't have to loop them, but I don't know if that would have an effect on the performance... Would there be other solutions? P.S. In the code, when I get the Move Cost, I check if the unit has to turn to perform the move, and the terrain type, nothing hard to do.

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• Estimating costs in a GOAP system

  - by fullwall

  I'm currently developing a GOAP system in Java. An explanation of GOAP can be found at http://web.media.mit.edu/~jorkin/goap.html. Essentially, it's using A* to plot between Actions that mutate the world state. To provide a fair chance for all Actions and Goals to execute, I'm using a heuristic function to estimate the cost of doing something. What is the best way to estimate this cost so that it is comparable to all the other costs? As an example, estimating the cost of running away from an enemy versus attacking it - how should the cost be calculated to be comparable?

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• Restricted pathfinding Area

  - by SubZeron

  So i'm triying to create a little "XCOM : Enemy Unknown" like game ,and using the Aron Granberg's Pathfinding-Tool (free version) to handle the "click to move part. i want to add a little trap system where the hero get stuck inside an area, so he will have only the possibility to move inside this trapped area, so far everything is fine however when i click outside the trapped area, the hero try to reach the destination even though the wall will prevents him from reaching it. so my question is, is there any way to restrict the area where the pathfinding system work to the trapped area dynamically. and wich Graph Type is recommended to use in this situation or this kind of Games (Grid Graph/Navmesh Graph/Point Graph). Thank you. image link for explanation : https://dl.dropbox.com/u/77993668/exemple.jpg

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• How can I plot a radius of all reachable points with pathfinding for a Mob (XNA)?

  - by PugWrath

  I am designing a tactical turn based game. The maps are 2d, but do have varying level-layers and blocking objects/terrain. I'm looking for an algorithm for pathfinding which will allow me to show an opaque shape representing all of the possible max-distance pixels that a mob can move to, knowing the mob's max pixel distance. Any thoughts on this, or do I just need to write a good pathfinding algorithm and use it to find the cutoff points for any direction in which an obstacle exists?

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