When I am creating a .sks scene in Xcode, I often need two nodes at the exact same x or y position to create a wall. I add rectangular physics bodies. They both have no friction whatsoever.
When I make a spritenode move over these collision bodies (I am using an impulse to the physics body) it acts as if there is a barrier between the two rectangles and I need to 'push' the node or make it jump to get over a boundary.
As I stated, these nodes are perfectly in line with each other so nodes should be able to flow past them smoothly.
Any suggestions?
If you need any code/pictures I am using, please ask.
Edit: The answer
My problem was the collision platforms were colliding with each other, and so they were slightly pushed out by on the generation of all platforms.
The way to solve is to set these following values on the platforms:
categoryBitMask to 1
collisionBitMask to 4294967294
which basically means they won't collide with each other.
Still new to swift, good to keep learning :P
I have already pointed #abc to the right answer. Just to explain why the masks are at 4294967295:
You can see that this is 32bits (all 1's with that number). Each bit is a different mask, and collisions and category masks look at these, to determine properties such as do they touch/collide. This means you have 32 masks you can make in your game.
If you want to understand how to make masks or combine masks, you can use Bitwise Operators. These operators can let you add masks together using the | (or) bitwise operator, or something similar. Please read the Apple Documentation I linked to.
Related
I'm thinking of making an online version of the game Sprouts, possibly using the JavaScript web browser graphics library p5.js
You can read more about it but basically there are 2 players that draw lines with their mouse between points. The lines can be straight or curved in any way. One of the rules is that no 2 lines can cross.
I haven't started making the game yet, but planning it ahead, everything seems relatively simple to accomplish except for one problem:
When a user draws a line, I need to figure out if this line intersects with another line. However, since these lines aren't linear or exactly mathematical in any way I'm used to, there doesn't seem to be a simple mathematical way I can check for intersection.
How would I check if two such lines, given that I know the location of every pixel on the lines, cross?
I apologize for no code, I haven't yet started it. If you wish to include code in your answer, you can use psuedocode or any gui programming that you might be familiar with. However, I would prefer a purely hypothetical answer, since everything is at this stage.
Here are some ideas I have:
For each pixel on the line, I could check if any of the other lines has a pixel of the same position, in which case they overlap. This seems inefficient, so the below point is something else I came up with that is more efficient but less rigid and reliable.
Before drawing the line, If you make sure all the lines are one color, for every pixel on the line, you could check if this pixel is already colored in the same color as the color of the lines, using something like getPixel() If so, abort drawing the line. This solutions seems prone to many problems and a bit fragile.
These two solutions either trade efficiency for reliability or vice-versa. Are there any other solutions you know? Keep in mind this will run in a browser, so efficiency is important.
Keep in mind this will run in a browser, so efficiency is important.
You need to give yourself a better idea of what kind of "efficiency" is important to you and your users. Both approaches you outlined seem reasonable to me. I wouldn't assume that a solution is inefficient before you try it and measure its performance.
Taking a step back, in general you're going to need to store the lines in some kind of data structure. You said the lines are not mathematical, but you can break the lines down into individual line segments or points, which are mathematical. That could be an array of line segments, or a 2D array of boolean values, or a map of points, or a quadtree. There are many options. Then you need to check for collisions between those lines or points and the new lines or points added by the other player.
Another option to consider is decreasing the resolution of your input space. For example, maybe your game window is 500x500 pixels, but you really only need the game board to be 100x100 possible point positions. You could scale that 100x100 game board up so it's displayed at 500x500. This would improve the "efficiency" of whatever solution you come up with.
But again, I wouldn't worry about "efficiency" at this point. Either solution you mentioned seems fine. Get that working and then iterate on it if you notice a problem. Good luck.
May be this article from Mike Bostock about the Sutherland-Hodgman algorythm can interest you. It is more related to the intersection of 2 polygons rather than 2 lines but may be it can be adapted to your problem.
I am making a version of the Atari game "Centipede" for my computer science class. I need help creating the collision for my code. I need to make it so when the bullets hit a part of the centipede, the game detects it and the part that got hit goes away.
This is a pretty broad question, but I'll try to help in a general sense.
You need to read up on collision detection.
First you probably want to break your centipede down into individual rectangles. For each rectangle, check whether it's colliding with the bullet.
You might consider point-rectangle collision detection, where you check whether the point is inside the rectangle. This will work if your bullet is a small point.
Or you might consider rectangle-rectangle collision detection, where you check whether two rectangles are overlapping. Use this if your bullets are larger than a point. Even if your bullet is a circle, you can usually get away with this kind of collision detection.
Please try something, and if you get stuck, then please post a MCVE that demonstrates where you're stuck. Good luck.
A simple implementation would be as follows:
1. Designate an array that represents the pixel positions of the centipede
2. Designate another array that represents the pixel positions of the bullet
3. Update each array's values based on the sampling rate of your game and check to see if there is any overlap. (Ideally have this as a separate thread)
4.Any overlap is indicative of a collision, so have some sort of collision handler function, which deletes the part of the centipede hit, that is triggered anytime an overlap event occurs.
I have an application where I need to move a number of objects around on the screen in a random fashion and they can not bump into each other. I'm looking for an algorithm that will allow me to generate the paths that don't create collisions and can continue for an indefinite time (i.e.: the objects keep moving around until a user driven event removes them from the program).
I'm not a game programmer but I think this looks like an AI problem and you guys probably solve it with your eyes closed. From what I've read A* seems to be the recommended 'basic idea' but I don't really want to invest a lot of time into it without some confirmation.
Can anyone shed some light on an approach? Anti-gravity movement maybe?
This is to be implemented on iOS, if that is important
New paths need to be generated at the end of each path
There is no visible 'grid'. Movement is completely free in 2D space
The objects are insects that walk around the screen until they are killed
A* is an algorithm to find the shortest path between a start and a goal configuration (in terms of whatever you define as short: common are e.g. euclidean distance, cost or time, angular distance...). Your insects seem not to have a specific goal, they don't even need a shortest path. I would certainly not go for A*. (By the way, since you are having a dynamic environment, D* would have been an idea - still it's meant to find a path from A to B).
I would tackle the problem as follows:
Random Paths and following them
For the random paths I see two methods. The first would be a simple random walk (click here to see a nice 2D animation with explanations), which can suffer from jittering and doesn't look too nice. The second one needs a little bit more detailed explanations.
For each insect generate four random points around them, maybe starting on a sinusoid. With a spline interpolation generate a smooth curve between those points. Take care of having C1 (in 2D) or C2 (in 3D) continuity. (Suggestion: Hermite splines)
With Catmull-Rom splines you can find your configurations while moving along the curve.
An application of a similar approach can be found in this blog post about procedural racetracks, also a more technical (but still not too technical) explanation can be found in these old slides (pdf) from a computer animations course.
When an insect starts moving, it can constantly move between the second and third point, when you always remove the first and append a new point when the insect reaches the third, thus making that the second point.
If third point is reached
Remove first
Append new point
Recalculate spline
End if
For a smoother curve add more points in total and move somewhere in the middle, the principle stays the same. (Personally I only used this in fixed environments, it should work in dynamic ones as well though.)
This can, if your random point generation is good (maybe you can use an approach similar to the one provided in the above linked blog post, or have a look at algorithms on the PCG Wiki), lead to smooth paths all over the screen.
Avoid other insects
To avoid other insects, three different methods come to my mind.
Bug algorithms
Braitenberg vehicles
An application of potential fields
For the potential fields I recommend reading this paper about dynamic motion planning (pdf). It's from robotics, but fairly easy to apply to your problem as well. You can just use the robots next spline point as the goal and set its velocity to 0 to apply this approach. However, it might be a bit too much for your simple game.
A discussion of Braitenberg vehicles can be found here (pdf). The original idea was more of a technical method (drive towards or away from a light source depending on how your motor is coupled with the photo receptor) and is often used to show how we apply emotional concepts like fear and attraction to other objects. The "fear" behaviour is an approach used for obstacle avoidance in robotics as well.
The third and probably simplest method are bug algorithms (pdf). I always have problems with the boundary following, which is a bit tricky. But to avoid another insect, these algorithms - no matter which one you use (I suggest Bug 1 or Tangent Bug) - should do the trick. They are very simple: Move towards your goal (in this application with the catmull-rom splines) until you have an obstacle in front. If the obstacle is close, change the insect's state to "obstacle avoidance" and run your bug algorithm. If you give both "colliding" insects the same turn direction, they will automatically go around each other and follow their original path.
As a variation you could just let them turn and recalculate a new spline from that point on.
Conclusion
Path finding and random path generation are different things. You have to experiment around what looks best for your insects. A* is definitely meant for finding shortest paths, not for creating random paths and following them.
You cannot plan the trajectories ahead of time for an indefinite duration !
I suggest a simpler approach where you just predict the next collision (knowing the positions and speeds of the objects allows you to tell if they will collide and when), and resolve it by changing the speed or direction of either objects (bounce before objects touch).
Make sure to redo a check for collisions in case you created an even earlier collision !
The real challenge in your case is to efficiently predict collisions among numerous objects, a priori an O(N²) task. You will accelerate that by superimposing a coarse grid on the play field and look at objects in neighboring cells only.
It may also be possible to maintain a list of object pairs that "might interfere in some future" (i.e. considering their distance and relative speed) and keep it updated. Checking that a pair may leave the list is relatively easy; efficiently checking for new pairs needing to enter the list is not.
Look at this and this Which described an AI program to auto - play Mario game.
So in this link, what the author did was using a A* star algorithm to guide Mario Get to the right border of the screen as fast as possible. Avoid being hurt.
So the idea is for each time frame, he will have an Environment which described the current position of other objects in the scene and for each action (up, down left, right and do nothing) , he calculate its cost function and made a decision of the next movement based on this.
Source: http://www.quora.com/What-are-the-coolest-algorithms
For A* you would need a 2D-Grid even if it is not visible. If I get your idea right you could do the following.
Implement a pathfinding (e.g. A*) then just generate random destination points on the screen and calculate the path. Once your insect reaches the destination, generate another destination point/grid-cell and proceed until the insect dies.
As I see it A* would only make sence if you have obstacles on the screen the insect should navigate around, otherwise it would be enough to just calculate a straight vector path and maybe handle collision with other insects/objects.
Note: I implemented A* once, later I found out that Lee's Algorithm
pretty much does the same but was easier to implement.
Consider a Hamiltonian cycle - the idea is a route that visits all the positions on a grid once (and only once). If you construct the cycle in advance (i.e. precalculate it), and set your insects off with some offset between them, they will never collide, simply because the path never intersects itself.
Also, for bonus points, Hamiltonian paths tend to 'wiggle about', and because it's a loop you can predict (and precalculate) the path into the indefinite future.
You can always use the nodes of the grid as knot points for a spline to smooth the movement, or even randomly shift all the points away from their strict 2d grid positions, until you have the desired motion.
Example Hamiltonian cycle from Wikimedia:
On a side note, if you want to generate such a path, consider constructing a loop through many points and just moving the points around in such a manner that they never intersect an existing edge. With some encouragement to move into gaps and away from each other, they should settle into some long, never-intersecting path. Store the result and use for your loop.
Let's say i want to create simple physics object with a shape of "matryoshka" or banal snowman . As i see it , i have two options to do it: 1. To create 2 circle (or may be custom) bodies and connect them with weld joint , or 2. To create one body with two circle (or may be custom) shapes in it.
So the question is: what is more expensive for CPU: bodies connected with joints or complicate-shaped bodies. If i have one object may be i don't feel difference in performance , but what if i have many object of that type?
I know that joints are expensive , but may be custom shaped bodies is more expensiver?
I'm working with Box2dFlash.
Since the question is about CPU use, joints use more CPU than shapes alone with no joint. Circles shapes can be more efficient than polygons in many cases, but not all.
For CPU optimization, use as few bodies and as simple polygons as possible. For every normal defined in a polygon, a calculation may need to be performed if an object overlaps with another. For circles, a maximum of one calculation is needed.
As an aside, unless you are already experiencing performance problems, you should not worry about if your shapes are the idea CPU use. Instead, you should ask whether the simulation the create is the one you want to happen. Box2D contains many many special case optimizations to make it run smoothly. You can also decrease its accuracy per tick by setting the velocity and position iteration variables. This will have a far greater effect on efficiency than geometry unless your geometry is extremely complex.
If you don't want the two sections of the snowman's body to move in relation to each other, then a single body is the way to go. You will ideally be defining the collision shape(s) manually anyway, so there is absolutely no gain to be had using a weld.
Think of it like this: If you use (a) weld(s), the collision shapes will be no less complicated than if you simply made an approximation of the collision geometry for a single body; it would still require either multiple collision shapes, or a single complex collision shape regardless of your choice. The weld will simply be adding an extra step.
If you need the snowman's body to be dynamic in anyway (break apart or flex) then a weld or regular joint is the way to go.
Greetings,
I'm working on a game project that uses a 3D variant of hexagonal tile maps. Tiles are actually cubes, not hexes, but are laid out just like hexes (because a square can be turned to a cube to extrapolate from 2D to 3D, but there is no 3D version of a hex). Rather than a verbose description, here goes an example of a 4x4x4 map:
(I have highlighted an arbitrary tile (green) and its adjacent tiles (yellow) to help describe how the whole thing is supposed to work; but the adjacency functions are not the issue, that's already solved.)
I have a struct type to represent tiles, and maps are represented as a 3D array of tiles (wrapped in a Map class to add some utility methods, but that's not very relevant).
Each tile is supposed to represent a perfectly cubic space, and they are all exactly the same size. Also, the offset between adjacent "rows" is exactly half the size of a tile.
That's enough context; my question is:
Given the coordinates of two points A and B, how can I generate a list of the tiles (or, rather, their coordinates) that a straight line between A and B would cross?
That would later be used for a variety of purposes, such as determining Line-of-sight, charge path legality, and so on.
BTW, this may be useful: my maps use the (0,0,0) as a reference position. The 'jagging' of the map can be defined as offsetting each tile ((y+z) mod 2) * tileSize/2.0 to the right from the position it'd have on a "sane" cartesian system. For the non-jagged rows, that yields 0; for rows where (y+z) mod 2 is 1, it yields 0.5 tiles.
I'm working on C#4 targeting the .Net Framework 4.0; but I don't really need specific code, just the algorithm to solve the weird geometric/mathematical problem. I have been trying for several days to solve this at no avail; and trying to draw the whole thing on paper to "visualize" it didn't help either :( .
Thanks in advance for any answer
Until one of the clever SOers turns up, here's my dumb solution. I'll explain it in 2D 'cos that makes it easier to explain, but it will generalise to 3D easily enough. I think any attempt to try to work this entirely in cell index space is doomed to failure (though I'll admit it's just what I think and I look forward to being proved wrong).
So you need to define a function to map from cartesian coordinates to cell indices. This is straightforward, if a little tricky. First, decide whether point(0,0) is the bottom left corner of cell(0,0) or the centre, or some other point. Since it makes the explanations easier, I'll go with bottom-left corner. Observe that any point(x,floor(y)==0) maps to cell(floor(x),0). Indeed, any point(x,even(floor(y))) maps to cell(floor(x),floor(y)).
Here, I invent the boolean function even which returns True if its argument is an even integer. I'll use odd next: any point point(x,odd(floor(y)) maps to cell(floor(x-0.5),floor(y)).
Now you have the basics of the recipe for determining lines-of-sight.
You will also need a function to map from cell(m,n) back to a point in cartesian space. That should be straightforward once you have decided where the origin lies.
Now, unless I've misplaced some brackets, I think you are on your way. You'll need to:
decide where in cell(0,0) you position point(0,0); and adjust the function accordingly;
decide where points along the cell boundaries fall; and
generalise this into 3 dimensions.
Depending on the size of the playing field you could store the cartesian coordinates of the cell boundaries in a lookup table (or other data structure), which would probably speed things up.
Perhaps you can avoid all the complex math if you look at your problem in another way:
I see that you only shift your blocks (alternating) along the first axis by half the blocksize. If you split up your blocks along this axis the above example will become (with shifts) an (9x4x4) simple cartesian coordinate system with regular stacked blocks. Now doing the raytracing becomes much more simple and less error prone.