I have cone->p (vertex of the cone), cone->orient (axis vector), cone->k (half-angle tangent), cone->minm and cone->maxm (2 height values, for cone caps). Also I have point intersection which is on the cone. How do I find the cone (side surface) normal vector at intersection point using only these parameters?
Сame up with simpler method:
Find distance Dis from intersection point I to base P
Make axis orientation vector of length
D = Dis * sqrt(1+k^2)
and make point on axis at this distance
A = P + Normalized(Orient) * D
Now
Normal = I - A
Old answer:
Make orthogonal projection of point I (intersection) onto cone axis using vector `IP = I - P' and scalar (dot) product:
AxProj = P + Orient * dot(IP, Orient) / dot(Orient, Orient)
Vector from AxPr to I (perpendicular to axis):
AxPerp = I - AxProj
Vector, tangent to cone surface, using vector product:
T = IP x AxPerp
Vector, normal to cone surface:
N = T x IP
If I is the intersection point on the cone's surface and you know its coordinates, and P is the vertex of the cone, whose coordinates you also know, then this is enough:
Normal = (axis x PI) x PI
Normal = Normal / norm(Normal)
where axis is the vector aligned with the axis of the cone.
Related
I have the green x,y points, how would I get the missing red?
You can rotate the two known points of 90° around their midpoint.
In pseudo code:
// Evaluate the midpoint from the coordinates of points a and b,
h_x = (b_x - a_x) / 2;
h_y = (b_y - a_y) / 2;
m_x = a_x + h_x;
m_y = a_y + h_y;
// Apply a rotation of 90 degree around the midpoint to find c and d
c_x = m_x - h_y;
c_y = m_y + h_x;
d_x = m_x + h_y;
d_y = m_y - h_x;
This result can be formally derived in terms of homogeneous coordinates and transfomation matrices.
The midpoint m, expressed in homogeneous coordinates, can be calculated as
To rotate a vector around the origin of an angle α, we apply a rotation matrix like
If another center of rotation is needed (the midpoint, in our case), we need to translate from the original position to the origin, apply the rotation and translate back again. The translation matrices are
The complete transformation can be expressed as
Where
So that we can evaluate, let's say d, with
Q.e.d.
I have three non-colinear 3D points, let's say pt1, pt2, pt3. I've computed the plane P using the sympy.Plane. How can I find the orientation of this plane(P) i.e. RPY(euler angles) or in quaternion?
I never used sympy, but you should be able to find a function to get the angle between 2 vectors (your normal vector and the world Y axis.)
theta = yaxis.angle_between(P.normal_vector)
then get the rotation axis, which is the normalized cross product of those same vectors.
axis = yaxis.cross(P.normal_vector).normal()
Then construct a quaternion from the axis and angle
q = Quaternion.from_axis_angle(axis, theta)
I am building a tilt-based Arduino device that needs to detect the "fall-line" vector of the device once it is tilted in a particular orientation. By "fall-line" I'll use the following example:
Imagine a frictionless plane with a point mass in the the middle of it and a 3-axis accelerometer mounted in the plane so that the x and y axes of the accelerometer are parallel to the plane. At rest, the plane is flat and the point mass does not move. Once the plane is tilted, the point mass will move in a particular direction at a given acceleration due to gravity. I need to calculate the angle in the x-y plane that the mass will move toward and a magnitude measure corresponding to the acceleration in that direction.
I realise this is probably simple Newtonian mechanics, but I have no idea how to work this out.
The direction of the "fall-line" and the magnitude of the acceleration are both determined by the projection of the gravitational pull vector onto the plane. If the plane has a normal vector n, then the projector operator is P( n ) = 1 - nn, where 1 is the identity operator and nn is the outer (tensor) product of the normal vector with itself. The projection of the gravitational pull vector g is simply g' = P( n ).g = (1 - nn) g = g - (n . g) n, where the dot denotes inner (dot) product. Now you only have to choose a suitable orthonormal reference frame (ex, ey, ez), where ei is a unit vector along direction i. In this reference frame:
n = nx ex + ny ey + nz ez
g = gx ex + gy ey + gz ez
The dot product n . g is then:
n . g = nx * gx + ny * gy + nz * gz
A very suitable choice of a reference frame is one where ez is collinear with n. Then nx = 0 and ny = 0 and nz = ||n|| = 1, because normal vectors are of unit length. In this frame n . g is simply gz. The components of the projection of g are then:
g'x = gx
g'y = gy
g'z = 0
The direction of g' in the XY plane can be determined by the fact that for the dot product in orthonormal reference frames a . b = ||a|| ||b|| cos(a, b), where ||a|| denotes the norm (length) of a and cos(a, b) is the cosine of the angle between a and b. If you measure the angle from the X direction, then:
g' . ex = (gx ex + gy ey) . ex = gx = ||g'|| ||ex|| cos(g', ex) = g' cos(g', ex)
where g' = ||g'|| = sqrt(gx^2 + gy^2). The angle is simply arccos(gx/g'), i.e. arc-cosine of the ratio between the X component of the gravity pull vector and the magnitude of its projection onto the XY plane:
angle = arccos[gx / sqrt(gx^2 + gy^2)]
The magnitude of the acceleration is proportional to the magnitude of g', which is (once again):
g' = ||g'|| = sqrt(gx^2 + gy^2)
Now the nice thing is that all accelerometers measure the components of the gravity field in a reference frame that usually have ex aligned with the height (or the width) of the device, the ex aligned with the width (or the height) of the device and ez is perpendicular to the surface of the device, which matches exactly the reference frame, where ez is collinear with the plane normal. If this is not the case with your Arduino device, simply rotate the accelerometer and align it as needed.
If i have a point (x,y,z) how to project it on to a sphere(x0,y0,z0,radius) (on its surface).
My input will be the coordinates of point and sphere.
The output should be the coordinates of the projected point on sphere.
Just convert from cartesian to spherical coordinates?
For the simplest projection (along the line connecting the point to the center of the sphere):
Write the point in a coordinate system centered at the center of the sphere (x0,y0,z0):
P = (x',y',z') = (x - x0, y - y0, z - z0)
Compute the length of this vector:
|P| = sqrt(x'^2 + y'^2 + z'^2)
Scale the vector so that it has length equal to the radius of the sphere:
Q = (radius/|P|)*P
And change back to your original coordinate system to get the projection:
R = Q + (x0,y0,z0)
Basically you want to construct a line going through the spheres centre and the point. Then you intersect this line with the sphere and you have your projection point.
In greater detail:
Let p be the point, s the sphere's centre and r the radius then x = s + r*(p-s)/(norm(p-s)) where x is the point you are looking for. The implementation is left to you.
I agree that the spherical coordinate approach will work as well but is computationally more demanding. In the above formula the only non-trivial operation is the square root for the norm.
It works if you set the coordinates of the center of the sphere as origin of the system (x0, y0, z0). So you will have the coordinates of the point referred to that origin (Xp', Yp', Zp'), and converting the coordinates to polar, you discard the radius (distance between the center of the sphere and the point) and the angles will define the projection.
I am rendering textured quads from an orthographic perspective and would like to simulate 'depth' by modifying UVs and the vertex positions of the quads four points (top left, top right, bottom left, bottom right).
I've found if I make the top left and bottom right corners y position be the same I don't get a linear 'skew' but rather a warped one where the texture covering the top triangle (which makes up the quad) seems to get squashed while the bottom triangles texture looks normal.
I can change UVs, any of the four points on the quad (but only in 2D space, it's orthographic projection anyway so 3D space won't matter much). So basically I'm trying to simulate perspective on a two dimensional quad in orthographic projection, any ideas? Is it even mathematically possible/feasible?
ideally what I'd like is a situation where I can set an x/y rotation as well as a virtual z 'position' (which simulates z depth) through a function and see it internally calclate the positions/uvs to create the 3D effect. It seems like this should all be mathematical where a set of 2D transforms can be applied to each corner of the quad to simulate depth, I just don't know how to make it happen. I'd guess it requires trigonometry or something, I'm trying to crunch the math but not making much progress.
here's what I mean:
Top left is just the card, center is the card with a y rotation of X degrees and right most is a card with an x and y rotation of different degrees.
To compute the 2D coordinates of the corners, just choose the coordinates in 3D and apply the 3D perspective equations :
Original card corner (x,y,z)
Apply a rotation ( by matrix multiplication ) you get ( x',y',z')
Apply a perspective projection ( choose some camera origin, direction and field of view )
For the most simple case it's :
x'' = x' / z
y'' = y' / z
The bigger problem now is the texturing used to get the texture coordinates from pixel coordinates :
The correct way for you is to use an homographic transformation of the form :
U(x,y) = ( ax + cy + e ) / (gx + hy + 1)
V(x,y) = ( bx + dy + f ) / (gx + hy + 1)
Which is fact is the result of the perpective equations applied to a plane.
a,b,c,d,e,f,g,h are computed so that ( with U,V in [0..1] ) :
U(top'',left'') = (0,0)
U(top'',right'') = (0,1)
U(bottom'',left'') = (1,0)
U(bottom'',right'') = (1,1)
But your 2D rendering framework probably uses instead a bilinear interpolation :
U( x , y ) = a + b * x + c * y + d * ( x * y )
V( x , y ) = e + f * x + g * y + h * ( x * y )
In that case you get a bad looking result.
And it is even worse if the renderer splits the quad in two triangles !
So I see only two options :
use a 3D renderer
compute the texturing yourself if you only need a few images and not a realtime animation.