On page 636 of the second edition, the second paragraph begins as follows:
Each object will have its own value of epsilon. […]
On page 637, equation 13.18 contains a term epsilon_a, and below it is written
The equation for j_b is similar, except that we substitute epsilon_b for epsilon_a.
The code on page 638 follows this by referring to m_Elasticity and other->m_Elasticity.
These assertions are incorrect. The coefficient of restitution is not a property of an individual object — it is a property of the collision itself. This can be seen clearly in equation 13.15, which applies to both objects. So if we are considering four materials A, B, C, and D, there would be six possible coefficients of restitution: A colliding with B, A colliding with C, A colliding with D, B colliding with C, B colliding with D, and C colliding with D.
Many thanks to James McGovern of the Art Institute of Vancouver for pointing this out.
An error that was corrected in the second edition, but is not noted in the errata for the first is in the equation for the impulse magnitude for rotational collision (Equation 12.24, page 618). The sum of cross products in the denominator should be dotted with the normalized collision normal.
And in both editions, the moments of inertia tensors used in the collision response equations (on pages 617-618 in the first edition, and page 639 in the second edition) are referred to as I_a and I_b. These should be J_a and J_b to match the previous notation used. The intent of this was to separate the notation for the identity matrix from the notation for the inertia tensor. However, standard convention is to use I for the inertia tensor, hence the typo.
Thanks for Johnny Newman, also of Vancouver, for discovering the latter two errors.
Apologies for any confusion any of this may have caused readers.
Hey, I noticed there there is not common xcode project in the 2nd edition disc.
Comment by gltovar — 5/23/2011 @ 10:28 pm
Hi,
love the book which I purchased last week. Please tell me if this is an error. On page 55 you refer to testing if ((v x w).(v x w)) is zero. Surely (a . a) is always zero?
regards
Don
Comment by Don McBrien — 5/28/2011 @ 6:11 pm
scratch that 🙁
a.a = |a|^2
Comment by Don McBrien — 5/28/2011 @ 8:11 pm
I was wondering if page 250 might also have an error. Shouldn’t the equation for x_v end with “- a” instead of “- 1”?
Also, the main website hasn’t been updated with a link to errata for the second edition.
Comment by Aapo Laitinen — 6/2/2011 @ 5:12 pm
hi , very well
Comment by fatima — 10/29/2011 @ 6:20 pm
I came across this on page 117 of the Second Edition: “There is a single solution only if the rank of A is equal to the minimum of the number of rows or columns of A.”
If I’m interpreting this correctly, it follows that a 2×3 coefficient matrix with a rank of 2 has a single solution. In reality, it has 1 free variable and thus infinitely many solutions. Shouldn’t there be a single solution only if the rank of A is equal to the number of unknowns, i.e. columns?
Thanks,
Jacob
Comment by Jacob — 12/14/2011 @ 11:10 am
Also, on page 126 it says: “The first part of the determinant sum is u_[0,0]*U~_[0,0].” Below, it displays this equation: “det(U) = u_[0,0]*U~_[0,0]”
Assuming I’m interpreting this correctly, this must be wrong. The determinant of a real matrix should be a real number, not another matrix. In both cases I think it means to say u_[0,0]*det(U~_[0,0]) — right?
Thanks,
Jacob
Comment by Jacob — 12/14/2011 @ 7:55 pm
Another one, haha — on page 130 it says: “It turns out the columns of R are the eigenvectors of A, and the diagonal elements of D are the corresponding eigenvectors.” Shouldn’t it be that “the diagonal elements of D are the corresponding eigenvalues”?
Thanks,
Jacob
Comment by Jacob — 12/14/2011 @ 8:18 pm
On page 180, the description in the first whole paragraph about rotating an object to demonstrate gimbal lock says to “rotate the object clockwise 90 degrees around an axis pointing forward … [then] rotate the new top of the object away from you by 90 degrees … [then] rotate the object counterclockwise 90 degrees around an axis point up …. The result is the same as pitching the object downward 90 degrees (see Figure 5.4).”
However, if I’m interpreting this correctly, the rotation described appears to be a fixed angle x-y-z (-pi/2,-pi/2,pi/2) rotation. The result of this is the same as pitching the object _upward_ 90 degrees. Furthermore, Figure 5.4 demonstrates a different rotation: a fixed angle x-y-z (pi/2,pi/2,pi/2) rotation.
Jacob
Comment by Jacob — 1/3/2012 @ 7:02 pm
I might be missing something here, but on pages 181-182 it says this: “Near-parallel vectors may cause us some problems either because the dot product is near 0, or normalizing the cross product ends up dividing by a near-zero value.”
For near-parallel vectors, wouldn’t the dot product be near +/- 1, not 0?
Thanks,
Jacob
Comment by Jacob — 1/3/2012 @ 7:05 pm
On page 178, under the heading “5.3.3 Concatenation” it says this: “Applying (pi/2, pi/2, pi/2) twice doesn’t end up at the same orientation as (pi, pi, pi).”
However, for fixed angle z-y-x (the most-recently mentioned convention in the book prior to this section), applying (pi/2, pi/2, pi/2) twice does appear to end up at the same orientation as (pi, pi, pi). This isn’t the case for fixed angle x-y-z, though (and presumably other conventions). That had me confused for a while!
Jacob
Comment by Jacob — 1/3/2012 @ 7:11 pm
On page 191, about halfway down the page, it mentions vectors w_0 and w_1, and then says that if we want to find the vector that lies halfway between them, we need to compute (w_1+w_2)/2. I’m assuming that it really means (w_0+w_1)/2?
As an aside, what is the significance of the division by 2? That is, using this method, what is the expected length of the resultant vector (without normalizing)? For instance, let w_0 = (1,0,0) and w_1 = (0,1,0). Then the halfway vector is (1+0,0+1,0+0)/2 = (0.5,0.5,0), whose length is 1/sqrt(2). Clearly this points in the correct direction, but its length is not the length of w_0, the length of w_1, or the average length of them, so what is it used for?
Thanks,
Jacob
Comment by Jacob — 1/3/2012 @ 7:23 pm
Could you please explain what is meant by the first matrix multiplication shown on page 138 in Section 4.2.3, Formal Representation [of affine transformations]?
For example, where did the matrix come from? Its entries are vectors, and the dimension of the product is (m+1)x1. What is the significance of the product, and how does it apply to what was just said?
I understand the matrix multiplication below it. In this case, the dimension of the product is 1×1 and, when expanded out, is equal to T(P). On initial reading it seems like the first matrix multiplication and the second one are supposed to be equivalent (before the second it says, “We can pull out the frame terms to get…”), but they’re clearly different, so how did you go from one to the other?
Thanks,
Jacob
Comment by Jacob — 1/4/2012 @ 4:58 pm
Equation 5.7 on page 191 has a hat over the q (i.e. unit quaternion notation). However, I don’t believe that it’s actually a unit quaternion–specifically, I think its length is something like 2*sqrt(2*cos(theta) + 2).
Thanks,
Jacob
Comment by Jacob — 1/4/2012 @ 8:02 pm
On page 191, when talking about converting from a rotation matrix to a quaternion, it says that “if the trace of the matrix is less than zero, then this will not work.” I was wondering if you could explain why?
While trying to figure out, I found another way of performing this conversion which may or may not be equivalent to your own method:
http://www.euclideanspace.com/maths/geometry/rotations/conversions/matrixToQuaternion/index.htm
In that case, it involves taking sqrt(Trace+1), so it actually fails if Trace+1<0. What is the difference between that method and your method which makes the difference between Trace<0 and Trace+1<0? Is it related to the fact that if the rotation was in a 4×4 affine transformation matrix then you'd get +1 when you take the trace?
Thanks,
Jacob
Comment by Jacob — 1/4/2012 @ 10:01 pm