First off, I am not after any instructions on logic for collision detection; I get it.
What I am trying to work out is the least complicated way to do this with Pygame using Sprites & Rects. I want to be able to check collisions for the Player against ground, walls & slopes. In theory it is quite straight forward, but I'm having difficulty because it seems like you cannot do this with one Rect.
One Rect is simple enough to get you collisions in the X plane against walls. The same Rect could be used also be used in the Y plane against solids, but not with slopes - since with the collision routines in Pygame it checks the whole Rect (or mask), rather than perhaps just the bottom middle of the Rect. It seems in addition you need to have a number of "sprites" to check collisions with, that are 1x1 pixel in various places around the Player.
What's the easiest way to do this, without having a bunch of 3, 4, or more separate "collision pixels" to check against slopes?
Geoff
It sound to me like you want pixel perfect collision detection. Here you can find a premade function that seems to me to be what you want/need.
You could use pygame.mask, which provides pixel perfect collision detection in C:
http://www.pygame.org/docs/ref/mask.html
Related
There was a gif on the internet where someone used some sort of CAD and drew multiple vector pictures in it. On the first frame they zoom-in on a tiny dot, revealing there a whole new different vector picture just on a different scale, and then they proceed to zoom-in further on another tiny dot, revealing another detailed picture, repeating several times. here is the link to the gif
Or another similar example: imagine you have a time-series with a granularity of a millisecond per sample and you zoom out to reveal years-worth of data.
My questions are: how such a fine-detailed data, in the end, gets rendered, when a huge amount of data ends up getting aliased into a single pixel.
Do you have to go through the whole dataset to render that pixel (i.e. in case of time-series: go through million records to just average them out into 1 line or in case of CAD render whole vector picture and blur it into tiny dot), or there are certain level-of-detail optimizations that can be applied so that you don't have to do this?
If so, how do they work and where one can learn about it?
This is a very well known problem in games development. In the following I am assuming you are using a scene graph, a node-based tree of objects.
Typical solutions involve a mix of these techniques:
Level Of Detail (LOD): multiple resolutions of the same model, which are shown or hidden so that only one is "visible" at any time. When to hide and show is usually determined by the distance between camera and object, but you could also include the scale of the object as a factor. Modern 3d/CAD software will sometimes offer you automatic "simplification" of models, which can be used as the low res LOD models.
At the lowest level, you could even just use the object's bounding
box. Checking whether a bounding box is in view is only around 1-7 point checks depending on how you check. And you can utilise object parenting for transitive bounding boxes.
Clipping: if a polygon is not rendered in the view port at all, no need to render it. In the GIF you posted, when the camera zooms in on a new scene, what is left from the larger model is a single polygon in the background.
Re-scaling of world coordinates: as you zoom in, the coordinates for vertices become sub-zero floating point numbers. Given you want all coordinates as precise as possible and given modern CPUs can only handle floats with 64 bits precision (and often use only 32 for better performance), it's a good idea to reset the scaling of the visible objects. What I mean by that is that as your camera zooms in to say 1/1000 of the previous view, you can scale up the bigger objects by a factor of 1000, and at the same time adjust the camera position and focal length. Any newly attached small model would use its original scale, thus preserving its precision.
This transition would be invisible to the viewer, but allows you to stay within well-defined 3d coordinates while being able to zoom in infinitely.
On a higher level: As you zoom into something and the camera gets closer to an object, it appears as if the world grows bigger relative to the view. While normally the camera space is moving and the world gets multiplied by the camera's matrix, the same effect can be achieved by changing the world coordinates instead of the camera.
First, you can use caching. With tiles, like it's done in cartography. You'll still need to go over all the points, but after that you'll be able zoom-in/zoom-out quite rapidly.
But if you don't have extra memory for cache (not so much actually, much less than the data itself), or don't have time to go over all the points you can use probabilistic approach.
It can be as simple as peeking only every other point (or every 10th point or whatever suits you). It yields decent results for some data. Again in cartography it works quite well for shorelines, but not so well for houses or administrative boarders - anything with a lot of straight lines.
Or you can take a more hardcore probabilistic approach: randomly peek some points, and if, for example, there're 100 data points that hit pixel one and only 50 hit pixel two, then you can more or less safely assume that if you'll continue to peek points still pixel one will be twice as likely to be hit that pixel two. So you can just give up and draw pixel one with a twice more heavy color.
Also consider how much data you can and want to put in a pixel. If you'll draw a pixel in black and white, then there're only 256 variants of color. And you don't need to be more precise. Or if you're going to draw a pixel in full color then you still need to ask yourself: will anyone notice the difference between something like rgb(123,12,54) and rgb(123,11,54)?
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/
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?
What exactly is the best way to detect 2d game collision? I use aabb's (axis-aligned-bounding-boxes) but if you have a big circle or something, you will be hitting it when your like 200 pixels away. Would the best way be to just see if the pixels in the 2 images are touching? please let me know a good method.
EDIT:
Ok so now I realize how simple circle collision is. but say I have an oval or something that isn't really a shape. Or even a square that is rotated 45 degrees.
If you have circles you can use Circle-To-Circle collision. Just take the distance of the midpoints and compare it with the length of the radii.
Beside that it really depends on what you need. There's a plethora of collision detection algorithms (mostly to speed things up, e.g. by using coherence between frames) but that's out of the range for a short general note and you'd need to specify your problem a bit more.
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.