my program includes increasing number of objects "n", each object has a custom-shape and coordinates .
To detect collision for each object i check the distance between it and all other objects to check if its close enough for collision.
however this would make complexity too high n^(n-1).
What would be a better algorithm for collision detection for :
-simple 2D objects like circles and triangles ?
-costume object made by vertices and PShape ?
Short answer: split your world space up into spaces, then only check objects that are in the same space. Think about it this way: if you have an object that's in the upper-left corner, you don't have to check that against objects in the lower-right corner. Just other objects in the upper-left corner.
There are many ways to implement this. One of the most common approaches is a data structure called a quadtree.
Another approach would be to use a physics library that does all of the collision detection for you.
The above two approaches might be overkill if you're just doing something simple though, so it's entirely up to you.
Related
I'm making a program that needs to detect the collision between 2 non-axis aligned boxes. My program only needs an indication if 2 non-axis aligned boxes are colliding. I would like to have the most simple and efficient algorithm possible.
Here I visualized the problem.
So as you can see squares 1,2 and 3 would return true because they collided with the green squares.
4 would return false because it isn't colliding.
I do have all the boxes of both colors in separate array lists.
Does anybody know a library or algorithm for this problem? Thanks in advance.
Check out the Area class in the java.awt.geom package.
http://docs.oracle.com/javase/6/docs/api/java/awt/geom/Area.html
I don't know how "easy" your game really is, how many shapes you'd have to check for (I'm thinking efficiency here), but if you have your different color shapes in different lists, a kind of brute force iteration may work for you. Not a clue if it would be efficient enough for you. I use box2D to tell me the collisions, but sounds like that may be overkill for you.
The brute force method I'm thinking of would be to utilize libgdx's Intersector class (check out the API, it has lots of methods). Iterate through your rectangles comparing to the others. Something like IntersectRectangles() gives you a boolean if two rectangles overlap (ie: collide).
This may be too inefficient/hacky, and a physics library may be too much. So one of the other answers provided may be the sweet spot.
A commonly-used approach involves quadtrees. There's a good write-up and tutorial here, which explains how to use quadtrees to perform collision detection in 2D space.
The general idea is that your game area will keep being partitioned by four as your add objects. Each partition is called a node and each node will maintain a reference to objects that exist in the corresponding partition. Objects are placed into nodes based on where they are in the 2D space. If a node does not fit cleanly into a partition, it is inserted into the parent node. Using this method, you don't have to perform an expensive check against every other object in your 2D space, because you can be sure that objects in different nodes (at the same level; i.e., sibling nodes) will not collide. So you only have to perform your collision detection on a small subset of objects.
Note that this just tells you which objects are occupying a certain area; it's a more efficient way to hone in on objects that are likely to be colliding. After that you have to check if the objects are actually colliding. There is another write-up here that goes over various techniques to accomplish this.
There are two algorithms/data-structures you need to consider for this problem:
A spatial data-structure to store your rotated quads, to efficiently determine which pairs of quads need to be tested against each other. Other answers have already addressed this. If the number of quads is small enough then you can just test all the red quads against all the green quads, which is O(m * n).
An algorithm to perform the actual test of one rotated quad against another. One of the simplest is the Separating Axis Theorem.
The basic idea behind the SAT is that if you can find at least one line where all the points of one convex object are on one side of it, and all the points of the other are on the other side, then the two are not colliding. The potential lines that you need to test are just the edges of both of the objects.
To implement it you need to implement a point-line test to tell you which side of an edge a point is on. This is done by calculating the normal to the edge, and then calculating the dot product of the edge normal and a vector from a point on the edge to the point you are testing. The sign of the dot product tells you which side the point is on (positive means the outside the edge, for an outward pointing normal). Whether you count zero (on the line) as outside or inside depends on whether you want objects that are just touching but not penetrating to count as a collision, if you do then the dot product must be greater than zero to count as outside.
For example if the points on objects are in clockwise order, and edgeA and edgeB are the two points of an edge on one object, and pointC is a point on the other object, the test is done like this (not using function calls, to show the math):
boolean isOutsideEdge(PointF edgeA, PointF edgeB, PointF pointC)
{
float normalX = edgeA.Y - edgeB.y;
float normalY = edgeB.X - edgeA.x;
float vectorX = pointC.x - edgeA.x;
float vectorY = pointC.y - edgeA.y;
return (normalX * vectorX) + (normalY * vectorY) > 0.0f;
}
Then the algorithm is:
For each edge on quad A, if all the corner points on quad B are on the outward facing side of the edge, then A and B are not colliding, stop processing and return false.
For each edge on quad B, if all the corner points on quad A are on the outward facing side of the edge, then A and B are not colliding, stop processing and return false.
If all those tests have been performed and none have returned false, then A and B are colliding, so return true.
The SAT can be generalized to arbitrary convex polygons.
So I decided to go with box2d in the end. This was the best solution because of the diffrent mask-qualifiers, the objects didn't collide but it could be easily checked wether they should be colliding.
I had to make my own contactlistener that overrides the default contactlistener. Here I could do anything if any 2 objects collided.
Thanks everyone for the help.
So, I'd like to figure out a function that allows you to determine if two cubes of arbitrary rotation and size intersect.
If the cubes are not arbitrary in their rotation (but locked to a particular axis) the intersection is simple; you check if they intersect in all three dimensions by checking their bounds to see if they cross or are within one another in all three dimensions. If they cross or are within in only two, they do not intersect. This method can be used to determine if the arbitrary cubes are even candidates for intersection, using their highest/lowest x, y, and z to create an outer bounds.
That's the first step. In theory, from that information we can tell which 'side' they are on from each other, which means we can eliminate some of the quads (sides) from our intersection. However, I can't assume that we have that information, since the rotation of the cubes may make it difficult to determine simply.
My thought is to take each pair of quads, find the intersection of their planes, then determine if that line intersects with at least one edge of each of the pairs of sides. If any pair of sides has a line of intersection that intersects with any of their edges, the quads intersect. If none intersect, the two cubes do not intersect.
We can then determine the depth of the intersection on the second cube by where the plane-intersection line intersects with its edge(s).
This is simply speculative, however. Is there a better, more efficient way to determine the intersection of these two cubes? I can think of a number of different ways to do this, and I can also tell that they could be very different in terms of amount of computation required.
I'm working in Java at the moment, but C/C++ solutions are cool too (I can port them); even psuedocode since it is perhaps a big question.
To find the intersection (contact) points of two arbitrary cubes in three dimensions, you have to do it in two phases:
Detect collisions. This is usually two phases itself, but for simplicity, let's just call it "collision detection".
The algorithm will be either SAT (Separating axis theorem), or some variant of polytope expansion/reduction. Again, for simplicity, let's assume you will be using SAT.
I won't explain in detail, as others have already done so many times, and better than I could. The "take-home" from this, is that collision detection is not designed to tell you where a collision has taken place; only that it has taken place.
Upon detection of an intersection, you need to compute the contact points. This is done via a polygon clipping algorithm. In this case, let's use https://en.wikipedia.org/wiki/Sutherland%E2%80%93Hodgman_algorithm
There are easier, and better ways to do this, but SAT is easy to grasp in 3d, and SH clipping is also easy to get your head around, so is a good starting point for you.
You should take a look at the field of computer graphics. They have many means. E.g. Weiler–Atherton clipping algorithm. There are also many datastructures that could ease up the process for you. To mention AABBs (Axis-aligned bounding boxes).
Try using the separating axis theorem. it should apply in 3d as it does in 2d.
If you create polygons from the sides of the cubes then another approach is to use Constructive Space Geometry (CSG) operations on them. By building a Binary Space Partitioning (BSP) tree of each cube you can perform an intersection on them. The result of the intersection is a set of polygons representing the intersection. In your case if the number of polygons is zero then the cubes don't intersect.
I would add that this approach is probably not a good real time solution, but you didn't indicate if this needed to happen in frame refresh time or not.
Since porting is an option you can look at the Javascript library that does CSG located at
http://evanw.github.io/csg.js/docs/
I've ported this library to C# at
https://github.com/johnmott59/CGSinCSharp
I tried to find out thousands of point in million polygon via web services .At first i implemented the algorithm(Point in polygon) in java ,but it take a long time .And then i split the table in mysql and tried to using the multiple thread to solve it ,but still inefficiently. Is there any faster algorithm or implementation for solve this?
Plus description about the polygon. 2D ,static,complex polygon(also with hole).
Any Suggestion will be appreciate.
Testing a point against a million polygons is going to take a lot of time, no matter how efficient your point in polygon function is.
You need to narrow down the search list. Start by making a bounding box for each polygon and only selecting the polygons when the point is within the bounding box.
If the polygons are unchanging you could convert each polygon to a set of triangles. Testing to see if a point is in a triangle should be much faster than testing to see if it's in an arbitrary polygon. Even though the number of triangles will be much larger than the number of polygons, it might be faster overall.
If the collection of polygons is static it may be helpful to first register them onto a spatial data structure - an R-tree might be a good choice, assuming that the polygons do not overlap each other too much.
To test a point against the polygon collection the enclosing leaf in the tree would first be found (an O(log(n)) style operation) and then it would only be necessary to perform the full point-in-polygon test for the polygons that are associated with the enclosing leaf.
This approach should greatly speed up each point test, but requires an additional setup phase to build the R-tree.
Hope this helps.
If you deal with millions of polygons, you need some kind of space partitioning, or it's gonna be slow, no matter how optimized your hit-test function is or how many threads work on solving your query.
What kind of space partitioning ? it depends:
2D? 3D?
Is your polygon set static? If not, do it changes frequently?
What kind of request are you doing on this set?
What kind of polygon is it? Triangle? Convex? Concave? Complex? With holes?
We need more information to help you.
EDIT
Here is a simple space partitioning scheme.
Suppose there is a Cartesian grid over your 2D space with a given step.
When you add a polygon:
Compute its bounding box
Find all the grid cells that intersect with the bounding box
For each cell, add a line in a special table.
The table looks like this: cell_x, cell_y, polygon_id. Add the proper indexes (at least cell_x and cell_y)
Of course, you want to choose your grid step so most of the polygons lay in less than 10 cells, or else your cell table will quickly becomes huge.
It's now easy to find the polygons at a given point:
Compute in which cell your point belongs
Get all polygons associated to this cell
For each polygon, use your hit-test function
This solution is far from optimal, but easy to implements.
I thik here is the case where divide and conquer would do, you could try making subpolyons or simplifying some of the poonts, maybe try an heuristic approach, there are my 5 cents.
Im making a game in Java with a few other people but we are stuck on one part of it, making the collision detection. The game is an RPG and I know how to do the collision detection with the characters using Rectangles, but what I dont know how to do is the collision detection for the maps. What I mean by that is like so the character cant walk over trees or water and that stuff but using rectangles doesnt seem like the best option here.
Well to explain what the game maps are gonna look like, here is an example http://i980.photobucket.com/albums/ae287/gordsmash/7-8.jpg
Now I could use rectangles to get bounds and stop the player from walking over the trees and water but that would take a lot of them.
But is there another easier way to prevent the player from walking over the trees and obstacles besides using Rectangles?
Here's a simple way but it uses more memory and you do the work up front... just create a background collision mask that denotes the permissible areas for characters to walk on in a binary form. You can store that in some sort of compressed bitmap form. The lookup then is very simple and very quick.
Rectangle collision detection seems to make sense; However, alternatively you may also try sphere-sphere collision detection, which can detect collision much quicker. You don't even need a square root for distance computations since you can compare the squared distances to see if the spheres overlap. This is a very fast method, and given the nature of your game could work very well.
ALSO! Assuming you have numerous tiles which you are colliding against, consider some method of spacial partitioning. Let me give you an easy example - subdivide your map into several rectangles (http://www.staff.ncl.ac.uk/qiuhua.liang/Research/Pic_research/mine_grid.jpg) and then depending on which rectangular area your player is currently residing in - check collision only against the tiles which are located within that area.
You may take it a step further - if you have more tiles in any given area than the threshold that you set - subdivide that area further to make more smaller areas within it.
The idea behind such subdivision is called Quadtree, and there is a huge quantity of papers and tutorials on the subject, you'll catch on very quickly.
Please let me know if you have any questions.
There are many solutions to this type of problem, but for what you're doing I believe the best course of action would be to use a tile engine. This would have been commonly used in similar games in the past (think any RPG on the SNES) and it provides you with a quick and easy means of both level/map design and collision detection.
The basic concept of a tile engine is that objects are stored in a 2D array and when your player (or any other moving game entity) attempts to move into a new tile you perform a simple check to see if the object in that tile is passable or not (for instance, if it's grass, the player may move; if it's a treasure chest, the player cannot move). This will greatly simplify checking for collisions (as a naive check of a list of entities will have O(n^2) performance). This picture might give you an idea of what I'm talking about. The lines have been added to illustrate a point, but of course when you're playing the game you don't actively think of everything as being composed of individual 32x32 pixel tiles.
While I don't personally have any experience with tile engines in Java, it looks like Mappy supports Java, and I've heard good things about PulpCore. You're more than welcome to create your own engine, of course, but you have to decide if your effort is better spent reinventing the wheel (but, of course, it will be your wheel then, and that is rather satisfying) or spend your time making a better game.
Hey, I'm currently trying to extract information from a 3d array, where each entry represents a coordinate in order to draw something out of it. The problem is that the array is ridiculously large (and there are several of them) meaning I can't actually draw all of it.
What I'm trying to accomplish then, is just to draw a representation of the outside coordinates, a shell of the array if you'd like. This array is not full, can have large empty spaces with only a few pixels set, or have large clusters of pixel data grouped together. I do not know what kind of shape to expect (could be a simple cube, or a complex concave mesh), and am struggling to come up with an algorithm to effectively extract the border. This array effectively stores a set of points in a 3d space.
I thought of creating 6 2d meshes (one for each side of the 3d array), and getting the shallowest point they can find for each position, and then drawing them separetly. As I said however, this 3d shape could be concave, which creates problems with this approach. Imagine a cone with a circle on top (said circle bigger than the cone's base). While the top and side meshes would get the correct depth info out of the shape, the bottom mesh would connect the base to the circle through vertical lines, making me effectivelly loose the conical shape.
Then I thought of annalysing the array slice by slice, and creating 2 meshes from the slice data. I believe this should work for any type of shape, however I'm struggling to find an algorithm which accuratly gives me the border info for each slice. Once again, if you just try to create height maps from the slices, you will run into problems if they have any concavities. I also throught of some sort of edge tracking algorithm, but the array does not provide continuous data, and there is almost certainly not a continuous edge along each slice.
I tried looking into volume rendering, as used in medical imaging and such, as it deals with similar problems to the one I have, but couldn't really find anything that I could use.
If anyone has any experience with this sort of problem, or any valuable input, could you please point me in the right direction.
P.S. I would prefer to get a closed representation of the shell, thus my earlier 2d mesh approach. However, an approach that simply gives me the shell points, without any connection between them, that would still be extremely helpful.
Thank you,
Ze
I would start by reviewing your data structure. As you observed, the array does not maintain any obvious spatial relationships between points. An octree is a pretty good representation for data like you described. Depending upon the complexity of you point set, you may be able to find the crust using just the octree - assuming you have some connectivity between near points.
Alternatively, you may then turn to more rigorous algorithms like raycasting or marching cubes.
Guess, it's a bit late by now to be truly useful to you, but for reference I'd say this is a perfect scenario for volumetric modeling (as you guessed yourself). As long as you know the bounding box of your point cloud, you can map these coordinates to a voxel space and increase the density (value) of each voxel for each data point. Once you have your volume fully defined, you can then use the Marching cubes algorithm to produce a 3D surface mesh for a given threshold value (iso value). That resulting surface doesn't need to be continuous, but will wrap all voxels with values > isovalue inside. The 2D equivalent are heatmaps... You can refine the surface quality by adjusting the iso threshold (higher means tighter) and voxel resolution.
Since you're using Java, you might like to take a look at my toxiclibs volumeutils library, which also comes with sevaral examples (for Processing) showing the general approach...
Imagine a cone with a circle on top
(said circle bigger than the cone's
base). While the top and side meshes
would get the correct depth info out
of the shape, the bottom mesh would
connect the base to the circle through
vertical lines, making me effectivelly
loose the conical shape.
Even an example as simple as this would be impossible to reconstruct manually, let alone algorithmically. The possibility of your data representing a cylinder with a cone shaped hole is as likely as the vertices representing a cone with a disk attached to the top.
I do not know what kind of shape to
expect (could be a simple cube...
Again, without further information on how the data was generated, 8 vertices arranged in the form of a cube might as well represent 2 crossed squares. If you knew that the data was generated by, for example, a rotating 3d scanner of some sort then that would at least be a start.