Want to decrease time to get the result
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When I tried to run my code, it takes more than a minute. I don't know why it takes much time like that.
Changing the tolerance might be one option.
Can anyone help me with this?
Thanks.
function a_new = manipul(a_initial)
options = optimoptions('fmincon','Display','iter');
A= [1 0 0; 0 1 0; 0 0 1];
B= [15; 15 ; 20];
a_new = fmincon(@rfs, a_initial, A, B,[],[],[],[],[], options);
initialR = SerialLink([0 0 4 0; 0 0 5 0;0 0 8 0], 'name', 'Initial Robot');
L(1) = Link([0 0 a_new(1,1) 0]);
L(2) = Link([0 0 a_new(1,2) 0]);
L(3) = Link([0 0 a_new(1,3) 0]);
newR = SerialLink(L, 'name', 'Optimized Robot');
T_1 = transl([30,20,0]);
T_2 = transl([20,25,0]);
T_3 = transl([27,8,0]);
T_4 = transl([23,5,0]);
T_5 = transl([25,23,0]);
q0 = [ 0 0 0 ];
q_final_1 = newR.ikcon(T_1); % Inverse kinematics solution with given disred position 1
q_final_2 = newR.ikcon(T_2); % Inverse kinematics solution with given disred position 2
q_final_3 = newR.ikcon(T_3); % Inverse kinematics solution with given disred position 3
q_final_4 = newR.ikcon(T_4); % Inverse kinematics solution with given disred position 4
q_final_5 = newR.ikcon(T_5); % Inverse kinematics solution with given disred position 5
t=0:.1:2;
traj1=jtraj(q0,q_final_1,t);
traj2=jtraj(q_final_1,q_final_2,t);
traj3=jtraj(q_final_2,q_final_3,t);
traj4=jtraj(q_final_3,q_final_4,t);
traj5=jtraj(q_final_4,q_final_5,t);
figure(1)
plot(30,20,'b*', 20,25,'b*', 27,8,'b*', 23,5, 'b*', 25,23, 'b*')
initialR.plot(traj1, 'workspace', [-40 40 -40 40 -40 40])
initialR.plot(traj2)
initialR.plot(traj3)
initialR.plot(traj4)
initialR.plot(traj5)
figure(2)
plot(30,20,'b*', 20,25,'b*', 27,8,'b*', 23,5, 'b*', 25,23, 'b*')
newR.plot(traj1)
newR.plot(traj2)
newR.plot(traj3)
newR.plot(traj4)
newR.plot(traj5)
end
function costFun = rfs(a_initial)
L(1) = Link([0 0 a_initial(1,1) 0]);
L(2) = Link([0 0 a_initial(1,2) 0]);
L(3) = Link([0 0 a_initial(1,3) 0]);
R = SerialLink(L,'name', 'My Robot');
% Expressing the desired position in homogeneous matrix
T_1 = transl([15,20,0]);
T_2 = transl([20,25,0]);
T_3 = transl([27,8,0]);
T_4 = transl([23,5,0]);
T_5 = transl([25,3,0]);
q_new_1 = R.ikcon(T_1); % Inverse kinematics solution with given disred position 1
q_new_2 = R.ikcon(T_2); % Inverse kinematics solution with given disred position 2
q_new_3 = R.ikcon(T_3); % Inverse kinematics solution with given disred position 3
q_new_4 = R.ikcon(T_4); % Inverse kinematics solution with given disred position 4
q_new_5 = R.ikcon(T_5); % Inverse kinematics solution with given disred position 5
T_real_1 = R.fkine(q_new_1); % Forward kinematics solution / initial position for the end effector
T_real_2 = R.fkine(q_new_2);
T_real_3 = R.fkine(q_new_3);
T_real_4 = R.fkine(q_new_4);
T_real_5 = R.fkine(q_new_5);
% Error between initial position and 5 desired position
costFun = (T_real_1.t(1,1) - T_1(1,4))^2 + (T_real_1.t(2,1) - T_1(2,4))^2 + (T_real_1.t(3,1) - T_1(3,4))^2 +...
(T_real_2.t(1,1) - T_2(1,4))^2 + (T_real_2.t(2,1) - T_2(2,4))^2 + (T_real_2.t(3,1) - T_2(3,4))^2 + ...
(T_real_3.t(1,1) - T_3(1,4))^2 + (T_real_3.t(2,1) - T_3(2,4))^2 + (T_real_3.t(3,1) - T_3(3,4))^2 + ...
(T_real_4.t(1,1) - T_4(1,4))^2 + (T_real_4.t(2,1) - T_4(2,4))^2 + (T_real_4.t(3,1) - T_4(3,4))^2 + ...
(T_real_5.t(1,1) - T_5(1,4))^2 + (T_real_5.t(2,1) - T_5(2,4))^2 + (T_real_5.t(3,1) - T_5(3,4))^2;
end
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2018-3-6
2018-3-6
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