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Pathfinding avoid a list of polygon

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Hello, i'm working on a 2D RTS project, no tile-based map. I have a problem on building map data structure & algorithm for that. I already think of a naive algorithm to solve that. Of course it's very slow. I'm looking for an advice from who experienced  biggrin.png

At very first, i have a list of obstacle as polygon like that

 

[attachment=20213:map.png]

 

i decided to build a pathfinding graph, then i travel all pairs of node, connect them if the connection segment doesn't intersect any polygon. this process have O(n^2) time complexity.

 

[attachment=20214:graph.png]

 

after that, on every path query, i try connect every node to A(startnode) and B(goal node), then do dijstra to find path. this process have O(2n) + O(nlogn) time complexity.

 

[attachment=20216:query graph.png]

 

[attachment=20217:path.png]

 

 

That's all, my algorithm works fine(even it's slow) if the environment is static, no insert, remove obstacle. But when the environment turn to dynamic, such as a obstacle removed, i need to rebuild pathfinding graph(O(n^2)), my fps extremely decreased, 120 to 10.

 

Is there a more professional aproach to solve my problem?

Edited by ngoaho91

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Consider using A-star instead of dijkstra, it'll be a lot faster, and requires only a small modification to dijkstra's to make it work.

 

Secondly, don't rebuild the path every frame. Maybe space the rebuilds over 60 frames (1 second apart). You might even do it in a background thread so the main thread can continue with processing the game, and take over the newly generated graph once its ready.

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Dynamically changing environments are tough for algorithms like yours and navmeshes.  Though Navmeshes do have some algorithms out there for recutting the mesh dynamically with decent performance, so it might be worth looking into.

 

But if you are really changing your environment a lot, you might have to fall back to a tilegrid.

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@cormet, actually the algorithm build & rebuild graph cause the slow. dijstra are works fine here but i will try a*.

@aardvajk, i was think of that way before, as i see from here, http://www.ai-blog.net/archives/000152.html the generated graph are poor. so when the agents growns, many paths should duplicate. then agents would collide many times. then evade process occurs frequencely and slow down the game.

@ferrous: please show me those algorithms :D

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That's all, my algorithm works fine(even it's slow) if the environment is static, no insert, remove obstacle. But when the environment turn to dynamic, such as a obstacle removed, i need to rebuild pathfinding graph(O(n^2)), my fps extremely decreased, 120 to 10.


For your tests, what is N? How many nodes are in your scene? There's two general approaches I would take:

1) You could reduce the number of number of connections you attempt to make within your scene by not actually checking all pairs.

2) You could reduce the cost of making each connection, by working on the collision algorithm or potentially the cost of constructing the graph itself.

Also, it is really N-squared? You're traveling all pairs. That's N-squared alone. Then, for each one, you have this condition "if the connection segment doesn't intersect any polygon". That does not sound like a constant-time condition. How do you collide a line segment against a polygon? How do you search for which polygons to test?

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@pink horror: i tested with 65 nodes, and do the test 100 times per frame, i'm too lazy to draw a map 6500 nodes biggrin.png. and yeah right, i forgot to mention intersect condition.

 

 


How do you collide a line segment against a polygon?

first i do simple step, collide the aabb of them. if overlap, i do complex step, check collide that line segment to every single line segment of the polygon.

 

 


How do you search for which polygons to test?

i'm using quad tree to divide polygon set. the time to find which polygons to test seem cost logN time(n=number of polygon)

Edited by ngoaho91

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i'm using quad tree to divide polygon set. the time to find which polygons to test seem cost logN time(n=number of polygon)

If you already have a quad tree, you already have a kind of waypoint system, much like a grid.

 

Just regard all quads in the tree, which do not intersect with a polygon and which parent is either the root or an quad which intesects a polygon. 

Place a waypoint in the center of each of those quads and at the mid of shared edges (choose the shorter edge if quads of different sizes share an edge).

Connect all waypoints on the edges with the waypoint at the center of the according quads.

 

If you change the terrain (modify polygons) you just need to regard the affected quad tree sections.

Edited by Ashaman73

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Why don't you use the good old grid + A* pathfinding?

 

It is a pretty simple approach, limit the amount of paths calculated and you should have an OK FPS rate.

 

If you need better approachs you will have to look for a better graph representation for A* than a grid.

 

I suggest reading:

http://theory.stanford.edu/~amitp/GameProgramming/ (A LOT of information on A*)

http://theory.stanford.edu/~amitp/GameProgramming/MapRepresentations.html (Map representation only)

Edited by KnolanCross

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Alright so you have three major steps to use navmeshes.

 

1.  navmesh generation

  You can do this manually if you want, or try to autogenerate it yourself, or get a thirdparty library (Recast/Detour)

  This looks like a decent article to start with: http://critterai.org/projects/nmgen_study/

 

2.  navmesh traversal (this is basically A* with some smoothing, a lot of the same algorithms apply)

  Check Knolan's links above, they do have a Navmesh entry

3.  Navmesh cutting

  Unfortunately I'm having trouble finding good links, I know there "Dynamically Updating a Navigation Mesh via Efficient Polygon Subdivision" by Paul Marden and Forrest Smith (AI Game Programming Wisdom 4), but that book is out of print, and uh, yeah, $599 for a used copy is insane.  (I have no idea why there isn't an e-book version out there for purchase)

There is this paper: http://users.ices.utexas.edu/~acook/papers/CAVW_Dynamic_ECM.pdf, and it's accompanying video http://www.youtube.com/watch?v=tH9dNESH4ic

Edited by ferrous

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Why don't you use the good old grid + A* pathfinding?

 

It is a pretty simple approach, limit the amount of paths calculated and you should have an OK FPS rate.

 

If you need better approachs you will have to look for a better graph representation for A* than a grid.

 

I suggest reading:

http://theory.stanford.edu/~amitp/GameProgramming/ (A LOT of information on A*)

http://theory.stanford.edu/~amitp/GameProgramming/MapRepresentations.html (Map representation only)

 

i'm not that good to make grid movement smooth biggrin.png. i compare AOE to starcraft, i think both use grid map, but starcraft has micro skill, AOE not. smooth unit movement is important for micro.

 

 

 


Alright so you have three major steps to use navmeshes.

 

i searched and found people talking about navigation mesh, but i don't understand why there are so many nodes that doesn't belong to any obstacle. i think a shortest path never travel through them. why are they there?

Edited by ngoaho91

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i compare AOE to starcraft, i think both use grid map, but starcraft has micro skill, AOE not.

StarCraft 2 uses navigation meshes with A* and a funnel algorithm for pathfinding. Unless you're talking about StarCraft 1, which used a 2D grid and A*.

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yeah, starcraft 2 is my goal, i'm talking about it's terrain and moving system. i'm already have a set of 2D assets that can form the game. but building assets can't fit in grid. i mean it's shape isn't square or rectangle or diamond, so i think of 'polygon' solution above. but it's seem unofficial and no one do it. i feel a little awkward

Edited by ngoaho91

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As mentioned multiple times, use navigation meshes, they're your best bet.

Is there a more professional aproach to solve my problem?

The following are two libraries. Recast Navigation generates navigation meshes and Detour is a powerful pathfinder, capable of searching for paths as well as handling the movement of agents.

https://github.com/memononen/recastnavigation

 

With that you can

  1. Automatically re-generate navigation meshes on the fly.
  2. Search paths for different sized agents.
  3. Control movement of agents using advanced flocking algorithms.

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