I'm following an example in a Processing book describing how to calculate nonorthogonal collisions (a ball bouncing on a non-horizontal plane), however, I don't really understand the logic behind these four expressions.
float groundXTemp = cosine * deltaX + sine * deltaY;
float groundYTemp = cosine * deltaY - sine * deltaX;
float velocityXTemp = cosine * velocity.vx + sine * velocity.vy;
float velocityYTemp = cosine * velocity.vy - sine * velocity.vx;
They're supposed to be calculating temporary values for the ground coordinates and velocity of the ball to calculate the collision as if it were orthogonal. Cosine and sine are the values for the rotation of the ground, and the velocity variables are the velocity of the ball. I can't grok what the expressions are actually doing to make the ground horizontal, and the book doesn't explain it very well. Any help would be appreciated.
These expressions are traditional expressions of a rotation. If you take a point (x,y), and you rotate it by an angle theta, you will obtain a point (x',y') with coordinates :
x' = cos(theta)*x - sin(theta)*y
y' = sin(theta)*x + cos(theta)*y
In your case, let's say that theta is the angle of the ground, you want to do the inverse rotation (so with angle -theta) to make the ground horizontal, this is why the sign is different from the formula above (cos(-theta) = cos(theta) and sin(-theta) = -sin(theta)).
If you want to go into details, check : http://en.wikipedia.org/wiki/Rotation_matrix
Related
I'm trying to create a solar system simulation, and I'm having problems trying to figure out initial velocity vectors for random objects I've placed into the simulation.
Assume:
- I'm using Gaussian grav constant, so all my units are AU/Solar Masses/Day
- Using x,y,z for coordinates
- One star, which is fixed at 0,0,0. Quasi-random mass is determined for it
- I place a planet, at a random x,y,z coordinate, and its own quasi-random mass determined.
Before I start the nbody loop (using RK4), I would like the initial velocity of the planet to be such that it has a circular orbit around the star. Other placed planets will, of course, pull on it once the simulation starts, but I want to give it the chance to have a stable orbit...
So, in the end, I need to have an initial velocity vector (x,y,z) for the planet that means it would have a circular orbit around the star after 1 timestep.
Help? I've been beating my head against this for weeks and I don't believe I have any reasonable solution yet...
It is quite simple if you assume that the mass of the star M is much bigger than the total mass of all planets sum(m[i]). This simplifies the problem as it allows you to pin the star to the centre of the coordinate system. Also it is much easier to assume that the motion of all planets is coplanar, which further reduces the dimensionality of the problem to 2D.
First determine the magnitude of the circular orbit velocity given the magnitude of the radius vector r[i] (the radius of the orbit). It only depends on the mass of the star, because of the above mentioned assumption: v[i] = sqrt(mu / r[i]), where mu is the standard gravitational parameter of the star, mu = G * M.
Pick a random orbital phase parameter phi[i] by sampling uniformly from [0, 2*pi). Then the initial position of the planet in Cartesian coordinates is:x[i] = r[i] * cos(phi[i]) y[i] = r[i] * sin(phi[i])
With circular orbits the velocity vector is always perpendicular to the radial vector, i.e. its direction is phi[i] +/- pi/2 (+pi/2 for counter-clockwise (CCW) rotation and -pi/2 for clockwise rotation). Let's take CCW rotation as an example. The Cartesian coordinates of the planet's velocity are:vx[i] = v[i] * cos(phi[i] + pi/2) = -v[i] * sin(phi[i])vy[i] = v[i] * sin(phi[i] + pi/2) = v[i] * cos(phi[i])
This easily extends to coplanar 3D motion by adding z[i] = 0 and vz[i] = 0, but it makes no sense, since there are no forces in the Z direction and hence z[i] and vz[i] would forever stay equal to 0 (i.e. you will be solving for a 2D subspace problem of the full 3D space).
With full 3D simulation where each planet moves in a randomly inclined initial orbit, one can work that way:
This step is equal to step 1 from the 2D case.
You need to pick an initial position on the surface of the unit sphere. See here for examples on how to do that in a uniformly random fashion. Then scale the unit sphere coordinates by the magnitude of r[i].
In the 3D case, instead of two possible perpendicular vectors, there is a whole tangential plane where the planet velocity lies. The tangential plane has its normal vector collinear to the radius vector and dot(r[i], v[i]) = 0 = x[i]*vx[i] + y[i]*vy[i] + z[i]*vz[i]. One could pick any vector that is perpendicular to r[i], for example e1[i] = (-y[i], x[i], 0). This results in a null vector at the poles, so there one could pick e1[i] = (0, -z[i], y[i]) instead. Then another perpendicular vector can be found by taking the cross product of r[i] and e1[i]:e2[i] = r[i] x e1[i] = (r[2]*e1[3]-r[3]*e1[2], r[3]*e1[1]-r[1]*e1[3], r[1]*e1[2]-r[2]*e1[1]). Now e1[i] and e2[i] can be normalised by dividing them by their norms:n1[i] = e1[i] / ||e1[i]||n2[i] = e2[i] / ||e2[i]||where ||a|| = sqrt(dot(a, a)) = sqrt(a.x^2 + a.y^2 + a.z^2). Now that you have an orthogonal vector basis in the tangential plane, you can pick one random angle omega in [0, 2*pi) and compute the velocity vector as v[i] = cos(omega) * n1[i] + sin(omega) * n2[i], or as Cartesian components:vx[i] = cos(omega) * n1[i].x + sin(omega) * n2[i].xvy[i] = cos(omega) * n1[i].y + sin(omega) * n2[i].yvz[i] = cos(omega) * n1[i].z + sin(omega) * n2[i].z.
Note that by construction the basis in step 3 depends on the radius vector, but this does not matter since a random direction (omega) is added.
As to the choice of units, in simulation science we always tend to keep things in natural units, i.e. units where all computed quantities are dimensionless and kept in [0, 1] or at least within 1-2 orders of magnitude and so the full resolution of the limited floating-point representation could be used. If you take the star mass to be in units of Solar mass, distances to be in AUs and time to be in years, then for an Earth-like planet at 1 AU around a Sun-like star, the magnitude of the orbital velocity would be 2*pi (AU/yr) and the magnitude of the radius vector would be 1 (AU).
Just let centripetal acceleration equal gravitational acceleration.
m1v2 / r = G m1m2 / r2
v = sqrt( G m2 / r )
Of course the star mass m2 must be much greater than the planet mass m1 or you don't really have a one-body problem.
Units are a pain in the butt when setting up physics problems. I've spent days resolving errors in seconds vs timestep units. Your choice of AU/Solar Masses/Day is utterly insane. Fix that before anything else.
And, keep in mind that computers have inherently limited precision. An nbody simulation accumulates integration error, so after a million or a billion steps you will certainly not have a circle, regardless of the step duration. I don't know much about that math, but I think stable n-body systems keep themselves stable by resonances which absorb minor variations, whether introduced by nearby stars or by the FPU. So the setup might work fine for a stable, 5-body problem but still fail for a 1-body problem.
As Ed suggested, I would use the mks units, rather than some other set of units.
For the initial velocity, I would agree with part of what Ed said, but I would use the vector form of the centripetal acceleration:
m1v2/r r(hat) = G m1 m2 / r2 r(hat)
Set z to 0, and convert from polar coordinates to cartesian coordinates (x,y). Then, you can assign either y or x an initial velocity, and compute what the other variable is to satisfy the circular orbit criteria. This should give you an initial (Vx,Vy) that you can start your nbody problem from. There should also be quite a bit of literature out there on numerical recipes for nbody central force problems.
I've managed to get Chipmunk physics and some other stuff to lay down a ball on my screen, and I can affect the gravity with some buttons / accelerometer. Yay me!
Next up, I'd like to turn off the gravity, and simulate a top-down view, where that ball moves around the screen of its own volition. I can apply forces to the ball using body -> f = cpv(dx, dy), but I'm not quite up on my physics and mathematics, so I'm trying to understand how the two values I feed it cause the movement.
I understand that positive values will move it right or down, and negative values will move it left or up, but that's about all I'm understanding at this point.
If I wanted to, say, pick a random compass bearing (0 - 359 degrees) and move it on that bearing, how would such a value translate into a vector?
I've created this method, but it's not working as expected and I'm unsure what I'm doing wrong:
- (CGPoint) getVectorFromAngle: (float) angle AndMagnitude: (float) magnitude
{
float x = magnitude * cos(angle);
float y = magnitude * sin(angle);
CGPoint point = CGPointMake(x, y);
NSLog(#"Made a CGPoint of X: %f and Y: %f.", point.x, point.y);
return point;
}
If I feed it an angle of 45 and a magnitude of 10, it creates X as 5.253220 and 8.509035. However, the calculator found here shows that it should create X and Y as 7.0711.
What do I have wrong here?
sin and cos take angles in radians, multiply your angles by π/180.
It's also good to point out that Chipmunk already contains a functions that do exactly what you want.
cpvmult(cpvforangle(radians), magnitude)
Consider a line from point A (x,y) to B (p,q).
The method CGContextMoveToPoint(context, x, y); moves to the point x,y and the method CGContextAddLineToPoint(context, p, q); will draw the line from point A to B.
My question is, can I find the all points that the line cover?
Actually I need to know the exact point which is x points before the end point B.
Refer this image..
The line above is just for reference. This line may have in any angle. I needed the 5th point which is in the line before the point B.
Thank you
You should not think in terms of pixels. Coordinates are floating point values. The geometric point at (x,y) does not need to be a pixel at all. In fact you should think of pixels as being rectangles in your coordinate system.
This means that "x pixels before the end point" does not really makes sense. If a pixel is a rectangle, "x pixels" is a different quantity if you move horizontally than it is if you move vertically. And if you move in any other direction it's even harder to decide what it means.
Depending on what you are trying to do it may or may not be easy to translate your concepts in pixel terms. It's probably better, however, to do the opposite and stop thinking in terms of pixels and translate all you are currently expressing in pixel terms into non pixel terms.
Also remember that exactly what a pixel is is system dependent and you may or may not, in general, be able to query the system about it (especially if you take into consideration things like retina displays and all resolution independent functionality).
Edit:
I see you edited your question, but "points" is not more precise than "pixels".
However I'll try to give you a workable solution. At least it will be workable once you reformulate your problem in the right terms.
Your question, correctly formulated, should be:
Given two points A and B in a cartesian space and a distance delta, what are the coordinates of a point C such that C is on the line passing through A and B and the length of the segment BC is delta?
Here's a solution to that question:
// Assuming point A has coordinates (x,y) and point B has coordinates (p,q).
// Also assuming the distance from B to C is delta. We want to find the
// coordinates of C.
// I'll rename the coordinates for legibility.
double ax = x;
double ay = y;
double bx = p;
double by = q;
// this is what we want to find
double cx, cy;
// we need to establish a limit to acceptable computational precision
double epsilon = 0.000001;
if ( bx - ax < epsilon && by - ay < epsilon ) {
// the two points are too close to compute a reliable result
// this is an error condition. handle the error here (throw
// an exception or whatever).
} else {
// compute the vector from B to A and its length
double bax = bx - ax;
double bay = by - ay;
double balen = sqrt( pow(bax, 2) + pow(bay, 2) );
// compute the vector from B to C (same direction of the vector from
// B to A but with lenght delta)
double bcx = bax * delta / balen;
double bcy = bay * delta / balen;
// and now add that vector to the vector OB (with O being the origin)
// to find the solution
cx = bx + bcx;
cy = by + bcy;
}
You need to make sure that points A and B are not too close or the computations will be imprecise and the result will be different than you expect. That's what epsilon is supposed to do (you may or may not want to change the value of epsilon).
Ideally a suitable value for epsilon is not related to the smallest number representable in a double but to the level of precision that a double gives you for values in the order of magnitude of the coordinates.
I have hardcoded epsilon, which is a common way to define it's value as you generally know in advance the order of magnitude of your data, but there are also 'adaptive' techniques to compute an epsilon from the actual values of the arguments (the coordinates of A and B and the delta, in this case).
Also note that I have coded for legibility (the compiler should be able to optimize anyway). Feel free to recode if you wish.
It's not so hard, translate your segment into a math line expression, x pixels may be translated into radius of a circe with center in B, make a system to find where they intercept, you get two solutions, take the point that is closer to A.
This is the code you can use
float distanceFromPx2toP3 = 1300.0;
float mag = sqrt(pow((px2.x - px1.x),2) + pow((px2.y - px1.y),2));
float P3x = px2.x + distanceFromPx2toP3 * (px2.x - px1.x) / mag;
float P3y = px2.y + distanceFromPx2toP3 * (px2.y - px1.y) / mag;
CGPoint P3 = CGPointMake(P3x, P3y);
Either you can follow this link also it will give you the detail description -
How to find a third point using two other points and their angle.
You can find out number of points whichever you want to find.
I am trying to calculate the forces that will act on circular objects in the event of a collision. Unfortunately, my mechanics is slightly rusty so i'm having a bit of trouble.
I have an agent class with members
vector position // (x,y)
vector velocity // (x,y)
vector forward // (x,y)
float radius // radius of the agent (all circles)
float mass
So if we have A,B:Agent, and in the next time step the velocity is going to change the position. If a collision is going to occur I want to work out the force that will act on the objects.
I know Line1 = (B.position-A.position) is needed to work out the angle of the resultant force but how to calculate it is baffling me when I have to take into account current velocity of the vehicle along with the angle of collision.
arctan(L1.y,L1.x) is am angle for the force (direction can be determined)
sin/cos are height/width of the components
Also I know to calculate the rotated axis I need to use
x = cos(T)*vel.x + sin(T)*vel.y
y = cos(T)*vel.y + sin(T)*vel.x
This is where my brain can't cope anymore.. Any help would be appreciated.
As I say, the aim is to work out the vector force applied to the objects as I have already taken into account basic physics.
Added a little psudocode to show where I was starting to go with it..
A,B:Agent
Agent {
vector position, velocity, front;
float radius,mass;
}
vector dist = B.position - A.position;
float distMag = dist.magnitude();
if (distMag < A.radius + B.radius) { // collision
float theta = arctan(dist.y,dist.x);
flost sine = sin(theta);
float cosine = cos(theta);
vector newAxis = new vector;
newAxis.x = cosine * dist .x + sine * dist .y;
newAxis.y = cosine * dist .y - sine * dist .x;
// Converted velocities
vector[] vTemp = {
new vector(), new vector() };
vTemp[0].x = cosine * agent.velocity.x + sine * agent.velocity.y;
vTemp[0].y = cosine * agent.velocity.y - sine * agent.velocity.x;
vTemp[1].x = cosine * current.velocity.x + sine * current.velocity.y;
vTemp[1].y = cosine * current.velocity.y - sine * current.velocity.x;
Here's to hoping there's a curious maths geek on stack..
Let us assume, without loss of generality, that we are in the second object's reference frame before the collision.
Conservation of momentum:
m1*vx1 = m1*vx1' + m2*vx2'
m1*vy1 = m1*vy1' + m2*vy2'
Solving for vx1', vy1':
vx1' = vx1 - (m2/m1)*vx2'
vy1' = vy1 - (m2/m1)*vy2'
Secretly, I will remember the fact that vx1'*vx1' + vy1'*vy1' = v1'*v1'.
Conservation of energy (one of the things elastic collisions give us is that angle of incidence is angle of reflection):
m1*v1*v1 = m1*v1'*v1' + m2*v2'+v2'
Solving for v1' squared:
v1'*v1' = v1*v1 - (m2/m1)v2'*v2'
Combine to eliminate v1':
(1-m2/m1)*v2'*v2' = 2*(vx2'*vx1+vy2'*vy1)
Now, if you've ever seen a stationary poolball hit, you know that it flies off in the direction of the contact normal (this is the same as your theta).
v2x' = v2'cos(theta)
v2y' = v2'sin(theta)
Therefore:
v2' = 2/(1-m2/m1)*(vx1*sin(theta)+vy1*cos(theta))
Now you can solve for v1' (either use v1'=sqrt(v1*v1-(m2/m1)*v2'*v2') or solve the whole thing in terms of the input variables).
Let's call phi = arctan(vy1/vx1). The angle of incidence relative to the tangent line to the circle at the point of intersection is 90-phi-theta (pi/2-phi-theta if you prefer). Add that again for the reflection, then convert back to an angle relative to the horizontal. Let's call the angle of incidence psi = 180-phi-2*theta (pi-phi-2*theta). Or,
psi = (180 or pi) - (arctan(vy1/vx1))-2*(arctan(dy/dx))
So:
vx1' = v1'sin(psi)
vy1' = v1'cos(psi)
Consider: if these circles are supposed to be solid 3D spheres, then use a mass proportional to radius-cubed for each one (note that the proportionality constant cancels out). If they are supposed to be disklike, use mass proportional to radius-squared. If they are rings, just use radius.
Next point to consider: Since the computer updates at discrete time events, you actually have overlapping objects. You should back out the objects so that they don't overlap before computing the new location of each object. For extra credit, figure out the time that they should have intersected, then move them in the new direction for that amount of time. Note that this time is just the overlap / old velocity. The reason that this is important is that you might imagine a collision that is computed that causes the objects to still overlap (causing them to collide again).
Next point to consider: to translate the original problem into this problem, just subtract object 2's velocity from object 1 (component-wise). After the computation, remember to add it back.
Final point to consider: I probably made an algebra error somewhere along the line. You should seriously consider checking my work.
I am trying to figure out if a latitude/longitude point is contained within a polygon defined by vertexes that represent points on the earth (also lat/lon's, in clockwise order). This is trivial for polygons that can be mapped to the 2D lat/lon space.
Where this becomes increasingly difficult is circle's (now switching back to 3D) that may go from pole to pole covering half the earth. The translation to lat/lon looks like a sine wave. The 2D point in polygon test no longer applies to this case. Is there an algorithm that exists that solves this problem?
================== Clarifications on comments below: ===================
The polygon is defined as (lon, lat) pairs in degrees, i.e., (60, 90), (60, 110), (-30, 110), (-30, 90).
I do have code that implements the ray casting algorithm, and that works. however, certain polygons on the surface of the earth do not translate to closed polygons in the 2D space.
As stated by denniston.t, if you are only interested in circles, and you have a radius, you can simply check if the Great Circle Distance between the center point and the point is less than the radius. To find the great circle distance you typically use the Haversine Formula. The following is my implementation in python:
from math import radians, sin, cos, asin, sqrt
def haversine(point1, point2):
"""Gives the distance between two points on earth.
The haversine formula, given two sets of latitude and longitude,
returns the distance along the surface of the earth in miles,
ignoring potential changes in elevation. The points must be in
decimal degrees.
"""
earth_radius_miles = 3956
lat1, lon1 = (radians(coord) for coord in point1)
lat2, lon2 = (radians(coord) for coord in point2)
dlat, dlon = (lat2 - lat1, lon2 - lon1)
a = sin(dlat/2.0)**2 + cos(lat1) * cos(lat2) * sin(dlon/2.0)**2
great_circle_distance = 2 * asin(min(1,sqrt(a)))
d = earth_radius_miles * great_circle_distance
return d
If you have the center point and radius of your circle drawn on the surface of the sphere, calculate the Great-circle distance between the center point and target point. If it's less than the radius of the circle, the target point lies in the circle.
This will not generalize to arbitrary polygons drawn on your sphere, but you only asked about circles, so I don't know if it matters to you.
containsLocation(point:LatLng, polygon:Polygon)