Vectorization of Operation inside Matrix
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DH is a 7*5 double.
The values in each row of DH are used for calculation in each loop.
To speed up, I've used pre-location. But can it be faster with vectorization?
DH = psm_m.DH;
n = size(DH,1);
T_i_All = zeros(4,4,n);
for i = 1:n
T_i_All (:,:,i)= [cos(DH(i,5)) -sin(DH(i,5)) 0 DH(i,3);
(sin(DH(i,5)))*(cos(DH(i,2))) (cos(DH(i,5)))*(cos(DH(i,2))) -sin(DH(i,2)) -(sin(DH(i,2)))*DH(i,4);
(sin(DH(i,5)))*(sin(DH(i,2))) (cos(DH(i,5)))*(sin(DH(i,2))) cos(DH(i,2)) (cos(DH(i,2)))*DH(i,4);
0 0 0 1];
end
I followed the MATLAB example
t = 0:.01:10; %example
y = sin(t); %example
But it doesn't work.
i=1:n;
T_i_All (:,:,i)= [cos(DH(i,5)) -sin(DH(i,5)) 0 DH(i,3);
(sin(DH(i,5)))*(cos(DH(i,2))) (cos(DH(i,5)))*(cos(DH(i,2))) -sin(DH(i,2)) -(sin(DH(i,2)))*DH(i,4);
(sin(DH(i,5)))*(sin(DH(i,2))) (cos(DH(i,5)))*(sin(DH(i,2))) cos(DH(i,2)) (cos(DH(i,2)))*DH(i,4);
0 0 0 1];
(Error using horzcat
Dimensions of matrices being concatenated are not consistent.)
Any help? Thanks!
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Accepted Answer
Guillaume
on 18 Dec 2018
First, permute DH so that the rows are in the 3rd dimension as in your output. Then you can vectorise your calculation:
DH = permute(psm_m.DH, [3 2 1]);
n = size(DH, 3);
T_i_All = [cos(DH(1, 5, :)), -sin(DH(1, 5, :)), repmat(0, 1, 1, n), DH(1, 3, :);
sin(DH(1, 5, :)).*cos(DH(1, 2, :)), cos(DH(1, 5, :)).*cos(DH(1, 2, :)), -sin(DH(1, 2, :)), -sin(DH(1, 2, :)).*DH(1, 4, :);
sin(DH(1, 5, :)).*sin(DH(1, 2, :)), cos(DH(1, 5, :)).*sin(DH(1, 2, :)), cos(DH(1, 2, :)), cos(DH(1, 2, :)).*DH(1, 4, :);
repmat([0 0 0 1], 1, 1, n)]
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