LibGDX - Rectangle collision detection in 2d? - vector

OK, I want to try this:
Make two cars (with sprites: e.g. red rectangle for car 1 texture, green rectangle for car 2 texture). With width: 32px and height: 20px.
(Movement of the cars are not the problem)
Then check collision detection like in the picture. The first is front crash and the second is side crash.
collision http://img802.imageshack.us/img802/2934/rectangles2.png
Then delete the sprites and only hold the vectors in the code. (position and rotation)
I want it so, because I want to add 3d Cars at these positions with his rotations.
I mean, Collision detection without sprites in 2d.
In the end game, there will be no sprites. Only 3d Objects.
Anybody has some codes for that?
I want to make it without Box2D. But when there is a good box 2d example. Then I can make it with box2d.
Thank You for any help.

Well if you want to do collision detection I would just use the included box2d. Have a look at Box2d Car Physics, this will give you a good starting point on how to build up the car.The code is for C however because LibGDX is a wrapper all methods that are demonstrated in the tutorial are available. If you need help setting up the box2d physics in libgdx the wiki is very good. To get started building your engine you should just use the box2d debugger provided with libgdx, This just draws all shapes (box/circle/polygon) then once your happy with the behaivour of your engine, you can just change the rendering code and use the X,Y positions and rotation of your car and use your 3d models.

Related

Implementing pathfinding in tiled 2d world

I have a 2d world made of tiles. Tiles are either passable, non-passable or have some sort of movement penalty.
All entities and tiles have their own hitboxes and sizes for collision detection.
Each tile tile has dimensions of 16x16px.
Most examples I've read seem to suggest that we're moving from center of one tile to the center of another tile. And as we see from the picture below, that red part looks hardly optimal nor it doesn't take entity size into account. Also pathding nodes are also placed into 2d array, with only 8 possible directions from each node.
But wouldn't actually shortest path be something like this?
How should I implement pathfinding?
Should tiles be splitted into smaller nodes for pathfinding or is there some other way to get more accurate routes? Even if I splitted each tile to have 10x10 pathfinding nodes, It still wouldn't find shortest line between 2 points.
Should there be more than 8 directions and if so, how should that be implemented?
For example if my world was 50x50 tiles big, how should the pathfinding map look like and how it should be generated?
It depends on your definition of "shortest path" and what you plan to do with it.
In your example, it appears that you consider a valid move to be from the center of one tile to the center of any other tile in unobstructed view. How you'd validate moves to partially obstructed tiles is not clear. This differs from the geometrically shortest path, which would obviously hug the wall, and the realistic shortest path, would would use a unit width and turn radius to avoid walls and sudden changes in direction.
A common approach is to use A* as usual, and then post-process the path in a number of ways to optimize and smooth it. This works both for grid based worlds like yours, and for more general navmeshes.
Gamasutra had a nice overview of this called Toward More Realistic Pathfinding, with a variety of ideas and techniques from smoothing zigzags and adding curves, to optimizing paths for units with acceleration and direction.
I had almost same problem and I have coded a pre-computation software for all tiles to all tiles with some optimization
You can find source code here : https://github.com/FurkanGozukara/pathfinding-2d-tile-map
The development video is here : https://www.youtube.com/watch?v=jRTA0iLjv6M
I did come up with my own algorithm and implementation. Therefore it is probably not the best nor the most optimized one. Although it is already implemented into my free browser based game MonsterMMORPG and it works great : https://www.monstermmorpg.com/

How does a non-tile based map works?

Ok, here is the thing. Recently i decided i wanted to understand how Random map generation works. I found some papers and some arguments. The most interesting one was "Diamond Square algorithm" and "Midpoint Displacement". I still have to try to apply those to a software, but other than that, i ran into this site: http://www-cs-students.stanford.edu/~amitp/game-programming/polygon-map-generation/
As you can see, the idea is to use polygons. But i have no idea how to apply that a Tile-Based map, not even how to create those polygons using the tools i have (c++ and sdl). I am assuming there is no way to do it ( please correct me if i am wrong.) But if i am not, how does a non-tile map works, and how are these polygons generated?
This answer will not give you directly the answers you're looking for, but hopefully will get you close enough!
The Problem
I think what blocks you is how to represent the data. You're probably used to a 2D grid that simply represent the type of each tile. As you know, this is fine to handle a tile-based map, but doesn't properly allow you to model worlds where tiles are of a different shape.
Graphs
What I suggest to you, is to see the problem a bit differently. A grid is nothing more than a graph (more info) with nodes that have 4 (or 8 if you allow diagonals) implicit neighbor nodes. So first, what I would do if I was you, would be to move from your strict standard 2D grid to a more "loose" graph, where each node has a position, a position, a list of neighbors (in most cases you'll have corners with 2 neighbors, borders with 3 and "middle" tiles with 4) and finally a rendering component which simply draws your tile on screen at the given position. Once this is done, you should be able to have the exact same results on screen that you currently have with your "2D Tile-Based" engine by simply calling the rendering component with each node who's bounding box (didn't touch it in what you should add to your node, but I'll get back to this later) intersects with the camera's frustum (in a 2D world, it would most likely if the position +/- the size intersects the RECT currently being drawn).
Search
The more generic approach will also help you doing stuff like pathfinding with generic algorithms that explore nodes until they find a valid path (see A* or Dijkstra). Even if you decided to stick to a good old 2D Tile Map game, these techniques would still be useful!
Yeah but I want Polygons
I hear you! So, if you want polygons, basically all you need to do, is add to your nodes a list of vertices and the appropriate data that you might need to render your polygons (either vertex color, textures and U/V maps, etc...) and update your rendering component to do the appropriate OpenGL (this for example should help) calls to draw your nodes. Once again, the first step to iteratively upgrade your 2D Tile Engine to a polygon map engine would be to, for each tile in your map, give each of your nodes two triangles, a texture resource (the tile), and U/V mappings (0,0 - 0,1 - 1,0 and 1,1). Once again, when this step is done, you should have a "generic" polygon based tile map engine. The creation of most of this data can be created procedurally by calculating coordinates based on tile position, tile size, etc...
Convex Polygons
If you decide that you ever might need NPCs to navigate on your map or want to allow your player to navigate by clicking the map, I would suggest that you always use convex polygons (the triangle being the simplest for of a convex polygon). This allows your code that assume that two different positions on the same polygon can be navigated to in straight line.
Complex Maps
Based on the link you provided, you want to have rather complex maps. In this case, the author used Voronoi Diagrams to generate the polygons of the map. There are already solutions to do triangulation like that, but you might also want to use other techniques that are easier to work with if you're just switching to 3D like this one for example. Once you have interesting results, you should consider implementing serialization to save/open your map data from the game. If you want to create an editor, be aware that it might be a lot of work but can be worth it if you want people to help you creating maps or to add elements to the maps (like geometry that's not part of the terrain).
I went all over the place with this answer, but hopefully it helps!
Just iterate over all the tiles, and do a hit-test from the centre of the tile to the polys. Turn the type of the tile into the type of the polygon. Did you need more than that?
EDIT: Sorry, I realize that probably isn't helpful. Playing with procedural algorithms can be fun and profitable. Start with a loop that iterates over all tiles and chooses randomly whether or not the tile is occupied. Then, iterate over them again and choose whether it is occupied or its neighbour is.
Also, check out the source code for this: http://dustinfreeman.org/toys/wall7-dustin.html

Vector Shape Difference & intersection

Let me explain my problem:
I have a black vector shape (let's say it's a series of joined, straight lines for now, but it'd be nice if I could also support quadratic curves).
I also have a rectangle of a predefined width and height. I'm going to place it on top of the black shape, and then take the union of the two.
My first issue is that I don't know how to quickly extract vector unions, but I think there is a well-defined formula I can figure out for myself.
My second, and more tricky issue is how to efficiently detect the position the rectangle needs to be in (i.e., what translation and rotation are needed by the matrices), in order to maximize the black, remaining after the union (see figure, below).
The red outlined shape below is ~33% black; the green is something like 85%; and there are positions for this shape & rectangle wherein either could have 100% coverage.
Obviously, I can brute-force this by trying every translation and rotation value for every point where at least part of the rectangle is touching the black shape, then keep track of the one with the most black coverage. The problem is, I can only try a finite number of positions (and may therefore miss the maximum). Apart from that, it feels very inefficient!
Can you think of a more efficient way of tackling this problem?
Something from my Uni days tells me that a Fourier transform might improve the efficiency here, but I can't figure out how I'd do that with a vector shape!
Three ideas that have promise of being faster and/or more precise than brute force search:
Suppose you have a 3d physics engine. Define a "cone-shaped" surface where the apex is at say (0,0,-1), the black polygon boundary on the z=0 plane with its centroid at the origin, and the cone surface is formed by connecting the apex with semi-infinite rays through the polygon boundary. Think of a party hat turned upside down and crumpled to the shape of the black polygon. Now constrain the rectangle to be parallel to the z=0 plane and initially so high above the cone (large z value) that it's easy to find a place where it's definitely "inside". Then let the rectangle fall downward under gravity, twisting about z and translating in x-y only as it touches the cone, staying inside all the way down until it settles and can't move any farther. The collision detection and force resolution of the physics engine takes care of the complexities. When it settles, it will be in a position of maximal coverage of the black polygon in a local sense. (If it settles with z<0, then coverage is 100%.) For the convex case it's probably a global maximum. To probabilistically improve the result for non-convex cases (like your example), you'd randomize the starting position, dropping the polygon many times, taking the best result. Note you don't really need a full blown physics engine (though they certainly exist in open source). It's enough to use collision resolution to tell you how to rotate and translate the rectangle in a pseudo-physical way as it twists and slides uniformly down the z axis as far as possible.
Different physics model. Suppose the black area is an attractive field generator in 2d following the usual inverse square rule like gravity and magnetism. Now let the rectangle drift in a damping medium responding to this field. It ought to settle with a maximal area overlapping the black area. There are problems with "nulls" like at the center of a donut, but I don't think these can ever be stable equillibria. Can they? The simulation could be easily done by modeling both shapes as particle swarms. Or since the rectangle is a simple shape and you are a physicist, you could come up with a closed form for the integral of attractive force between a point and the rectangle. This way only the black shape needs representation as particles. Come to think of it, if you can come up with a closed form for torque and linear attraction due to two triangles, then you can decompose both shapes with a (e.g. Delaunay) triangulation and get a precise answer. Unfortunately this discussion implies it can't be done analytically. So particle clouds may be the final solution. The good news is that modern processors, particularly GPUs, do very large particle computations with amazing speed. Edit: I implemented this quick and dirty. It works great for convex shapes, but concavities create stable points that aren't what you want. Using the example:
This problem is related to robot path planning. Looking at this literature may turn up some ideas In RPP you have obstacles and a robot and want to find a path the robot can travel while avoiding and/or sliding along them. If the robot is asymmetric and can rotate, then 2d planning is done in a 3d (toroidal) configuration space (C-space) where one dimension is rotation (so closes on itself). The idea is to "grow" the obstacles in C-space while shrinking the robot to a point. Growing the obstacles is achieved by computing Minkowski Differences.) If you decompose all polygons to convex shapes, then there is a simple "edge merge" algorithm for computing the MD.) When the C-space representation is complete, any 1d path that does not pierce the "grown" obstacles corresponds to continuous translation/rotation of the robot in world space that avoids the original obstacles. For your problem the white area is the obstacle and the rectangle is the robot. You're looking for any open point at all. This would correspond to 100% coverage. For the less than 100% case, the C-space would have to be a function on 3d that reflects how "bad" the intersection of the robot is with the obstacle rather than just a binary value. You're looking for the least bad point. C-space representation is an open research topic. An octree might work here.
Lots of details to think through in both cases, and they may not pan out at all, but at least these are frameworks to think more about the problem. The physics idea is a bit like using simulated spring systems to do graph layout, which has been very successful.
I don't believe it is possible to find the precise maximum for this problem, so you will need to make do with an approximation.
You could potentially render the vector image into a bitmap and use Haar features for this - they provide a very quick O(1) way of calculating the average colour of a rectangular region.
You'd still need to perform this multiple times for different rotations and positions, but it would bring it algorithmic complexity down from a naive O(n^5) to O(n^3) which may be acceptably fast. (with n here being the size of the different degrees of freedom you are scanning)
Have you thought to keep track of the remaining white space inside the blocks with something like if whitespace !== 0?

Math for a geodesic sphere

I'm trying to create a very specific geodesic tessellation, but I can't find anything online about it.
It is normal to subdivide the triangles of an icosahedron into triangle patches and project them onto the sphere. However, I noticed an animated GIF on the Wikipedia entry for Geodesic Domes that appears not to follow this scheme. Geodesic spheres generally comprise a mixture of mostly hexagonal triangle patches, with pentagonal patches forming at the vertices of the original icosahedron; in most cases, these pentagons are linked together; that is, following a straight edge from the center of one pentagon leads to the center of another pentagon. In the Wikipedia animation, however, the edge from the center of one pentagon doesn't appear to intersect the center of an adjacent pentagons; instead it intersects the side of the other pentagon.
Where can I go to learn about the math behind this particular geometry? Ideally, I'd like to know of an algorithm for generating such tessellations.
Marcelo,
The most-commonly employed geodesic tessellations are either Class-I or Class-II. The image you reference is of a Class-III tessellation, more-specifically, 4v{3,1}. The classes can be diagrammed, so:
Class-III tessellations are chiral, and can have left-handed or right-handed twist. Here's the mirror-image of the sample you referenced:
You can find some 3D models of Class-III spheres, at Google's 3D Warehouse:
http://sketchup.google.com/3dwarehouse/cldetails?mid=b926c2713e303860a99d92cd8fe533cd
Being properly identified should get you off to a good start.
Feel free to stop by the Geodesic Help Group; http://groups.google.com/group/GeodesicHelp?hl=en
TaffGoch
Here's an image from one of Joe Clinton's NASA publications:
I believe it is actually just a matter of resolution (i.e., number of sub-divisions). The tessellation you show does seem to emanate from an icosahedron scheme: cf p.7 here, mid-page example. Check out the rest of the document for some calculation details - also its cited references, and some further code samples here.
Marcelo,
If you want to devise algorithms to generate any class of geodesic spheres, you can do it here:
http://thomson.phy.syr.edu/thomsonapplet.htm
Start by using the "custom(m,n)" option, select your desired parameters, then hit the "pause" button. Switch to "lattice energy" and hit the "Auto" button.
If you're intimately familiar with java, you can save the "jar" file(s) for this app, and examine the contents, to back-engineer the algorithms.
BTW, this java app also has a "File" menu option, which can activate a new window, listing the "Point set" (vertex coordinates.) I copy & paste them into an Excel spreadsheet, from which I can generate a "csv" file that can be, subsequently, imported into 3D-graphic programs.
Taff

Implementing z-axis in a 2D side-scroller

I'm making a side scroller similar to Castle Crashers and right now I'm using SAT for collision detection. That works great, but I want to simulate level "depth" by allowing objects to move up and down on the screen, basically along a z-axis (like this screenshot http://favoniangamers.files.wordpress.com/2009/07/castle-crashers-ps3.jpg). This isn't an isometric game, but rather uses parallax scrolling.
I added a z component to my vector class, and I plan to cull collisions based on the 'thickness' of a shape and it's z position. I'm just not sure how calculate the positions of shapes for rendering or how to add jumping with gravity. How do I calculate the max y value (for the ground) as the z position changes? Basically it's the relationship of the z and y axis that confuses me.
I'd appreciate links to resources if anyone knows of this topic.
Thanks!
It's actually possible to make your collision detection algorithm dimensionally agnostic. Just have a collision detector that works along one dimension, use that to check each dimension, and your answer to "are these colliding or not" is the logical AND of the collision detection along each of the dimensions.
Your game should be organised to keep the interaction of game objects, and the rendering of the game to the screen completely seperate. You can think of these two sections of the program as the "model" and the "view". In the model, you have a full 3D world, with 3 axes. You can't go halvesies on this point without some level of pain. Your model must be proper 3D.
The view will read the location of all the game objects, and project them onto the screen using the camera definition. For this part you don't need a full 3D rendering engine. The correct technical term for the perspective you're talking about is "oblique", and it can be seen in many ancient chinese and japanese scroll paintings and prints- in particular look for images of "The Tale of Genji".
The on screen position of an object (including the ground surface!) goes something like this:
DEPTH_RATIO=0.5;
view_x=model_x-model_z*DEPTH_RATIO-camera_x;
view_y=model_y+model_z*DEPTH_RATIO-camera_y;
you can modify for a straight orthographic front projection:
DEPTH_RATIO=0.5;
view_x=model_x-camera_x;
view_y=model_y+model_z*DEPTH_RATIO-camera_y;
And of course don't forget to cull objects outside the volume defined by the camera.
You can also use this mechanism to handle the positioning of parallax layers for you. This is of course, a matter changing your camera to a 1-point perspective projection instead of an orthographic projection. You don't have to use this to change the rendered size of your sprites, but it will help you manage the x position of objects realistically. if you're up for a challenge, you could even mix projections- use 1 point perspective for deep backgrounds, and the orthographic stuff for the foreground.
You should separate your conceptual Y axis used by you physics calculation (collision detection etc.) and the Y axis you actually draw on the screen. That way it becomes less confusing.
Just do calculations per normal pretending there is no relationship between Y and Z axis then when you actually draw the object on the screen you simulate the Z axis using the Y axis:
screen_Y = Y + Z/some_fudge_factor;
Actually, this is how real 3d engines work. After all the world calculations are done the X, Y and Z coordinates are mapped onto screen_X and screen_Y via a function (usually a bit more complicated than the equation above, but just a bit).
For example, to implement pseudo-isormetric view in your game you can even apply Z to the screen_X axis so objects are displaced diagonally instead of vertically.

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