def retarget(self,source_joint_angles):
'''returns the retargeted target joint angles given the source joint
angles. '''
angles_matrix = np.matrix(source_joint_angles)
self.source = mlab.setJointAngles(self.source, angles_matrix)
self.target = mlab.easy_retarget(self.source, self.target)
return self.target.joints.angles
pr2_initial_angles = np.matrix([0,0,0,0])
pr2 = mlab.setJointAngles(pr2, pr2_initial_angles)
human_initial_angles = np.matrix([0,-110,40,-60])
human = mlab.setJointAngles(human, human_initial_angles)
# Visualize chains with the draw() function.
mlab.figure()
mlab.grid('on')
mlab.headSphere() #creates a dummy head that provides context.
mlab.draw(pr2,'k')
mlab.draw(human)
# ----------------------------------------------------------- #
# Retargeting Chains:
# ----------------------------------------------------------- #
# easy_retarget(source, target) abstracts away all the messy bits.
pr2_retargeted = mlab.easy_retarget(human, pr2)
# draw on the open figure:
mlab.draw(pr2_retargeted,'g')
mlab.title('Retargeting Demo')
mlab.legend('black - pr2 initial pose','blue - human source pose', 'green - pr2 retargeted pose')
