I am trying to draw a railway in the way it is implemented in railroad tycoon 3. I have understood some of the patterns by which this is done, but I cannot find a formula for their application. I am trying to build an arc using only two points and some initial direction. For simplicity, let's assume that I can only plot a path in the range from 0 to 90 degrees. The arc should always start in the direction of "Initial direction". I need a method that would implement this. I tried to depict the idea in the drawings. Any pseudocode would do I guess.
general idea
borderline case at alpha = 0
borderline case at alpha = 90 degrees
Center C lies at middle perpendicular to SE segment, so we should find vectors
se = (E.x - S.x, E.y - S.y)
perp = (-se.y, se.x) = (S.y - E.y, E.x - S.x) //MC direction
and middle point
M = ((E.x + S.x)/2, (E.y - S.y)/2)
and express C coordinates using parametric equation
C = M + perp*t
Note that initial arc direction d is perpendicular to radius CS, so their dot product is zero:
(C - S).dot.d = 0
(M.x + perp.x * t - S.x)*d.x + (M.y + perp.y * t - S.y)*d.y = 0
This is linear equation for unknown parameter t, after solving it we know center C and can build the arc.
Python code. Perhaps examples are too simple to reveal bugs, but the first with half-circle gives R=L/2, center at M, and the second one shows correct C position and R.
from math import hypot, atan2
def arcfromptsdir(sx, sy, ex, ey, dx, dy):
sex = ex - sx
sey = ey - sy
perpx = -sey
perpy = sex
mx = (ex + sx) / 2
my = (ey + sy) / 2
#equation
#(sex/2 + perpx * t )*dx + (sey/2 + perp.y * t )*dy = 0
p = perpx * dx + perpy * dy
if p:
t = -0.5*(sex*dx + sey*dx) / p
else:
return None
#centerx, centery, radius
cx = mx + perpx * t
cy = my + perpy * t
radius = hypot(cx-sx, cy-sy)
arcangle = atan2((sx-cx) * (ey-cy) - (sy-cy) * (ex-cx),
(sx-cx) * (ex-cx) + (sy-cy) * (ey-cy))
return (cx, cy, radius, arcangle)
print(arcfromptsdir(0, 0, 2, 0, 0, 1))
print(arcfromptsdir(0, 0, 2, 0, 0.7071, 0.7071))
(1.0, 0.0, 1.0, -3.141592653589793)
(1.0, -1.0, 1.4142135623730951, -1.5707963267948966)
I have a quaternion that contains the rotation of the three axes (x, y, z) at the same time.
I want to convert this quaternion to a rotation matrix but only the rotation on the Y axis of the quaternion or of any of the other axes, without all three at the same time.
A possible route:
Transform unit vectors X=(1,0,0) and Z=(0,0,1) by the quaternion
Call these rotated vectors (x0,x1,x2) and (z0,z1,z2)
If the rotation would have been purely around Y, we would have:
(x0,x1,x2) = (cos(theta), 0, sin(theta))
(z0,z1,z2) = (-sin(theta), 0, cos(theta))
not used is (y0,y1,y2) = (0, 1, 0)
so, calculate
c = (x0+z2) / 2
and s = (x2-z0) / 2
then normalize to get c2 + s2 equal to 1
norm = sqrt(c * c + s * s)
if norm != 0:
c = c / norm
s = s / norm
(if the norm would be zero, there is not much we can do)
the angle would be atan2(c, s)
the rotation matrix would be [[c,0,-s],[0,1,0],[s,0,c]]
I come accross a math problem about Interactive Computer Graphics.
I summarize and abstract this problem as follows:
I'm going to rotation a 3d coordinate P(x1,y1,z1) around a point O(x0,y0,z0)
and there are 2 vectors u and v which we already know.
u is the direction to O before transformation.
v is the direction to O after transformation.
I want to know how to conduct the calculation and get the coordinate of Q
Thanks a lot.
Solution:
Rotation About an Arbitrary Axis in 3 Dimensions using the following matrix:
rotation axis vector (normalized): (u,v,w)
position coordinate of the rotation center: (a,b,c)
rotation angel: theta
Reference:
https://docs.google.com/viewer?a=v&pid=sites&srcid=ZGVmYXVsdGRvbWFpbnxnbGVubm11cnJheXxneDoyMTJiZTZlNzVlMjFiZTFi
for just single point no rotations is needed ... so knowns are:
u,v,O,P
so we now the distance is not changing:
|P-O| = |Q-O|
and directions are parallel to u,v so:
Q = O + v*(|P-O|/|v|)
But I suspect you want to construct rotation (transform matrix) such that more points (mesh perhaps) are transformed. If that is true then you need at least one known to get this right. Because there is infinite possible rotations transforming P -> Q but the rest of the mesh will be different for each ... so you need to know at least 2 non trivial points pair P0,P1 -> Q0,Q1 or axis of rotation or plane parallel to rotation or any other data known ...
Anyway in current state you can use as rotation axis vector perpendicular to u,v and angle obtained from dot product:
axis = cross (u,v)
ang = +/-acos(dot(u,v))
You just need to find out the sign of angle so try both and use the one for which the resultinq Q is where it should be so dot(Q-O,v) is max. To rotate around arbitrary axis and point use:
Rodrigues_rotation_formula
Also this might be helpfull:
Understanding 4x4 homogenous transform matrices
By computing dot product between v and u get the angle l between the vectors. Do a cross product of v and u (normalized) to produce axis of rotation vector a. Let w be a vector along vector u from O to P. To rotate point P into Q apply the following actions (in pseudo code) having axis a and angle l computed above:
float4 Rotate(float4 w, float l, float4 a)
{
float4x4 Mr = IDENTITY;
quat_t quat = IDENTITY;
float4 t = ZERO;
float xx, yy, zz, xy, xz, yz, wx, wy, wz;
quat[X] = a[X] * sin((-l / 2.0f));
quat[Y] = a[Y] * sin((-l / 2.0f));
quat[Z] = a[Z] * sin((-l / 2.0f));
quat[W] = cos((-l / 2.0f));
xx = quat[X] * quat[X];
yy = quat[Y] * quat[Y];
zz = quat[Z] * quat[Z];
xy = quat[X] * quat[Y];
xz = quat[X] * quat[Z];
yz = quat[Y] * quat[Z];
wx = quat[W] * quat[X];
wy = quat[W] * quat[Y];
wz = quat[W] * quat[Z];
Mr[0][0] = 1.0f - 2.0f * (yy + zz);
Mr[0][1] = 2.0f * (xy + wz);
Mr[0][2] = 2.0f * (xz - wy);
Mr[0][3] = 0.0f;
Mr[1][0] = 2.0f * (xy - wz);
Mr[1][1] = 1.0f - 2.0f * (xx + zz);
Mr[1][2] = 2.0f * (yz + wx);
Mr[1][3] = 0.0f;
Mr[2][0] = 2.0f * (xz + wy);
Mr[2][1] = 2.0f * (yz - wx);
Mr[2][2] = 1.0f - 2.0f * (xx + yy);
Mr[2][3] = 0.0f;
Mr[3][0] = 0.0f;
Mr[3][1] = 0.0f;
Mr[3][2] = 0.0f;
Mr[3][3] = 1.0f;
w = Mr * w;
return w;
}
Point Q is at the end of the rotated vector w. Algorithm used in the pseudo code is quaternion rotation.
If you know u, v, P, and O then I would suggest that you compute |OP| which should be preserved under rotations. Then multiply this length by the unit vector -v (I assumed u, v are unit vectors: if not - normalize them) and translate the origin by this -|OP|v vector. The negative sign in front of v comes from the description given in your question:"v is the direction to O after transformation".
P and Q are at the same distance R to O
R = sqrt( (x1-x0)^2 + (y1-y0)^2 + (z1-z0)^2 )
and OQ is collinear to v, so OQ = v * R / ||v|| where ||v|| is the norm of v
||v|| = sqrt( xv^2 + yv^2 + zv^2 )
So the coordinates of Q(xq,yq,zq) are:
xq= xo + xv * R / ||v||
yq= yo + yv * R / ||v||
zq= zo + zv * R / ||v||
I have two vectors u and v. Is there a way of finding a quaternion representing the rotation from u to v?
Quaternion q;
vector a = crossproduct(v1, v2);
q.xyz = a;
q.w = sqrt((v1.Length ^ 2) * (v2.Length ^ 2)) + dotproduct(v1, v2);
Don't forget to normalize q.
Richard is right about there not being a unique rotation, but the above should give the "shortest arc," which is probably what you need.
Half-Way Vector Solution
I came up with the solution that I believe Imbrondir was trying to present (albeit with a minor mistake, which was probably why sinisterchipmunk had trouble verifying it).
Given that we can construct a quaternion representing a rotation around an axis like so:
q.w == cos(angle / 2)
q.x == sin(angle / 2) * axis.x
q.y == sin(angle / 2) * axis.y
q.z == sin(angle / 2) * axis.z
And that the dot and cross product of two normalized vectors are:
dot == cos(theta)
cross.x == sin(theta) * perpendicular.x
cross.y == sin(theta) * perpendicular.y
cross.z == sin(theta) * perpendicular.z
Seeing as a rotation from u to v can be achieved by rotating by theta (the angle between the vectors) around the perpendicular vector, it looks as though we can directly construct a quaternion representing such a rotation from the results of the dot and cross products; however, as it stands, theta = angle / 2, which means that doing so would result in twice the desired rotation.
One solution is to compute a vector half-way between u and v, and use the dot and cross product of u and the half-way vector to construct a quaternion representing a rotation of twice the angle between u and the half-way vector, which takes us all the way to v!
There is a special case, where u == -v and a unique half-way vector becomes impossible to calculate. This is expected, given the infinitely many "shortest arc" rotations which can take us from u to v, and we must simply rotate by 180 degrees around any vector orthogonal to u (or v) as our special-case solution. This is done by taking the normalized cross product of u with any other vector not parallel to u.
Pseudo code follows (obviously, in reality the special case would have to account for floating point inaccuracies -- probably by checking the dot products against some threshold rather than an absolute value).
Also note that there is no special case when u == v (the identity quaternion is produced -- check and see for yourself).
// N.B. the arguments are _not_ axis and angle, but rather the
// raw scalar-vector components.
Quaternion(float w, Vector3 xyz);
Quaternion get_rotation_between(Vector3 u, Vector3 v)
{
// It is important that the inputs are of equal length when
// calculating the half-way vector.
u = normalized(u);
v = normalized(v);
// Unfortunately, we have to check for when u == -v, as u + v
// in this case will be (0, 0, 0), which cannot be normalized.
if (u == -v)
{
// 180 degree rotation around any orthogonal vector
return Quaternion(0, normalized(orthogonal(u)));
}
Vector3 half = normalized(u + v);
return Quaternion(dot(u, half), cross(u, half));
}
The orthogonal function returns any vector orthogonal to the given vector. This implementation uses the cross product with the most orthogonal basis vector.
Vector3 orthogonal(Vector3 v)
{
float x = abs(v.x);
float y = abs(v.y);
float z = abs(v.z);
Vector3 other = x < y ? (x < z ? X_AXIS : Z_AXIS) : (y < z ? Y_AXIS : Z_AXIS);
return cross(v, other);
}
Half-Way Quaternion Solution
This is actually the solution presented in the accepted answer, and it seems to be marginally faster than the half-way vector solution (~20% faster by my measurements, though don't take my word for it). I'm adding it here in case others like myself are interested in an explanation.
Essentially, instead of calculating a quaternion using a half-way vector, you can calculate the quaternion which results in twice the required rotation (as detailed in the other solution), and find the quaternion half-way between that and zero degrees.
As I explained before, the quaternion for double the required rotation is:
q.w == dot(u, v)
q.xyz == cross(u, v)
And the quaternion for zero rotation is:
q.w == 1
q.xyz == (0, 0, 0)
Calculating the half-way quaternion is simply a matter of summing the quaternions and normalizing the result, just like with vectors. However, as is also the case with vectors, the quaternions must have the same magnitude, otherwise the result will be skewed towards the quaternion with the larger magnitude.
A quaternion constructed from the dot and cross product of two vectors will have the same magnitude as those products: length(u) * length(v). Rather than dividing all four components by this factor, we can instead scale up the identity quaternion. And if you were wondering why the accepted answer seemingly complicates matters by using sqrt(length(u) ^ 2 * length(v) ^ 2), it's because the squared length of a vector is quicker to calculate than the length, so we can save one sqrt calculation. The result is:
q.w = dot(u, v) + sqrt(length_2(u) * length_2(v))
q.xyz = cross(u, v)
And then normalize the result. Pseudo code follows:
Quaternion get_rotation_between(Vector3 u, Vector3 v)
{
float k_cos_theta = dot(u, v);
float k = sqrt(length_2(u) * length_2(v));
if (k_cos_theta / k == -1)
{
// 180 degree rotation around any orthogonal vector
return Quaternion(0, normalized(orthogonal(u)));
}
return normalized(Quaternion(k_cos_theta + k, cross(u, v)));
}
The problem as stated is not well-defined: there is not a unique rotation for a given pair of vectors. Consider the case, for example, where u = <1, 0, 0> and v = <0, 1, 0>. One rotation from u to v would be a pi / 2 rotation around the z-axis. Another rotation from u to v would be a pi rotation around the vector <1, 1, 0>.
I'm not much good on Quaternion. However I struggled for hours on this, and could not make Polaris878 solution work. I've tried pre-normalizing v1 and v2. Normalizing q. Normalizing q.xyz. Yet still I don't get it. The result still didn't give me the right result.
In the end though I found a solution that did. If it helps anyone else, here's my working (python) code:
def diffVectors(v1, v2):
""" Get rotation Quaternion between 2 vectors """
v1.normalize(), v2.normalize()
v = v1+v2
v.normalize()
angle = v.dot(v2)
axis = v.cross(v2)
return Quaternion( angle, *axis )
A special case must be made if v1 and v2 are paralell like v1 == v2 or v1 == -v2 (with some tolerance), where I believe the solutions should be Quaternion(1, 0,0,0) (no rotation) or Quaternion(0, *v1) (180 degree rotation)
Why not represent the vector using pure quaternions? It's better if you normalize them first perhaps.
q1 = (0 ux uy uz)'
q2 = (0 vx vy vz)'
q1 qrot = q2
Pre-multiply with q1-1
qrot = q1-1 q2
where q1-1 = q1conj / qnorm
This is can be thought of as "left division".
Right division, which is not what you want is:
qrot,right = q2-1 q1
From algorithm point of view , the fastest solution looks in pseudocode
Quaternion shortest_arc(const vector3& v1, const vector3& v2 )
{
// input vectors NOT unit
Quaternion q( cross(v1, v2), dot(v1, v2) );
// reducing to half angle
q.w += q.magnitude(); // 4 multiplication instead of 6 and more numerical stable
// handling close to 180 degree case
//... code skipped
return q.normalized(); // normalize if you need UNIT quaternion
}
Be sure that you need unit quaternions (usualy, it is required for interpolation).
NOTE:
Nonunit quaternions can be used with some operations faster than unit.
Some of the answers don't seem to consider possibility that cross product could be 0. Below snippet uses angle-axis representation:
//v1, v2 are assumed to be normalized
Vector3 axis = v1.cross(v2);
if (axis == Vector3::Zero())
axis = up();
else
axis = axis.normalized();
return toQuaternion(axis, ang);
The toQuaternion can be implemented as follows:
static Quaternion toQuaternion(const Vector3& axis, float angle)
{
auto s = std::sin(angle / 2);
auto u = axis.normalized();
return Quaternion(std::cos(angle / 2), u.x() * s, u.y() * s, u.z() * s);
}
If you are using Eigen library, you can also just do:
Quaternion::FromTwoVectors(from, to)
Working just with normalized quaternions, we can express Joseph Thompson's answer in the follwing terms.
Let q_v = (0, u_x, v_y, v_z) and q_w = (0, v_x, v_y, v_z) and consider
q = q_v * q_w = (-u dot v, u x v).
So representing q as q(q_0, q_1, q_2, q_3) we have
q_r = (1 - q_0, q_1, q_2, q_3).normalize()
According to the derivation of the quaternion rotation between two angles, one can rotate a vector u to vector v with
function fromVectors(u, v) {
d = dot(u, v)
w = cross(u, v)
return Quaternion(d + sqrt(d * d + dot(w, w)), w).normalize()
}
If it is known that the vectors u to vector v are unit vectors, the function reduces to
function fromUnitVectors(u, v) {
return Quaternion(1 + dot(u, v), cross(u, v)).normalize()
}
Depending on your use-case, handling the cases when the dot product is 1 (parallel vectors) and -1 (vectors pointing in opposite directions) may be needed.
The Generalized Solution
function align(Q, u, v)
U = quat(0, ux, uy, uz)
V = quat(0, vx, vy, vz)
return normalize(length(U*V)*Q - V*Q*U)
To find the quaternion of smallest rotation which rotate u to v, use
align(quat(1, 0, 0, 0), u, v)
Why This Generalization?
R is the quaternion closest to Q which will rotate u to v. More importantly, R is the quaternion closest to Q whose local u direction points in same direction as v.
This can be used to give you all possible rotations which rotate from u to v, depending on the choice of Q. If you want the minimal rotation from u to v, as the other solutions give, use Q = quat(1, 0, 0, 0).
Most commonly, I find that the real operation you want to do is a general alignment of one axis with another.
// If you find yourself often doing something like
quatFromTo(toWorldSpace(Q, localFrom), worldTo)*Q
// you should instead consider doing
align(Q, localFrom, worldTo)
Example
Say you want the quaternion Y which only represents Q's yaw, the pure rotation about the y axis. We can compute Y with the following.
Y = align(quat(Qw, Qx, Qy, Qz), vec(0, 1, 0), vec(0, 1, 0))
// simplifies to
Y = normalize(quat(Qw, 0, Qy, 0))
Alignment as a 4x4 Projection Matrix
If you want to perform the same alignment operation repeatedly, because this operation is the same as the projection of a quaternion onto a 2D plane embedded in 4D space, we can represent this operation as the multiplication with 4x4 projection matrix, A*Q.
I = mat4(
1, 0, 0, 0,
0, 1, 0, 0,
0, 0, 1, 0,
0, 0, 0, 1)
A = I - leftQ(V)*rightQ(U)/length(U*V)
// which expands to
A = mat4(
1 + ux*vx + uy*vy + uz*vz, uy*vz - uz*vy, uz*vx - ux*vz, ux*vy - uy*vx,
uy*vz - uz*vy, 1 + ux*vx - uy*vy - uz*vz, uy*vx + ux*vy, uz*vx + ux*vz,
uz*vx - ux*vz, uy*vx + ux*vy, 1 - ux*vx + uy*vy - uz*vz, uz*vy + uy*vz,
ux*vy - uy*vx, uz*vx + ux*vz, uz*vy + uy*vz, 1 - ux*vx - uy*vy + uz*vz)
// A can be applied to Q with the usual matrix-vector multiplication
R = normalize(A*Q)
//LeftQ is a 4x4 matrix which represents the multiplication on the left
//RightQ is a 4x4 matrix which represents the multiplication on the Right
LeftQ(w, x, y, z) = mat4(
w, -x, -y, -z,
x, w, -z, y,
y, z, w, -x,
z, -y, x, w)
RightQ(w, x, y, z) = mat4(
w, -x, -y, -z,
x, w, z, -y,
y, -z, w, x,
z, y, -x, w)