opt = FCOptimizer(frames, params.tf_target_points, est_base_H_target, est_cam_H_neck, fix_target_transform=True,
W=np.diag([1.0, 1.0, 10.0]))
new_est_base_H_target, new_est_cam_H_neck = opt.optimize()
opt.print_stats()
print np.dot(linalg.inv(new_est_cam_H_neck), est_cam_H_neck)
true_color = (1.0, 0.0, 1.0, 1.0)
initial_color = (0.0, 1.0, 1.0, 1.0)
estimated_color = (1.0, 1.0, 0.0, 1.0)
fcviz.draw_frames(upright_frames, est_cam_H_neck, 'new_initial_camera_poses', initial_color, cam_mark_lines=False)
fcviz.draw_target(est_base_H_target, 'estimated_target_pose', true_color)
fcviz.draw_frames(upright_frames, new_est_cam_H_neck, 'new_estimated_head_poses', estimated_color, cam_mark_lines=False)
# write out the resulting cal file to a urdf
urdf_path = os.path.join(
roslib.packages.get_pkg_dir("arm_robot_model"), "models/sensorsValues.urdf.xacro")
print 'Cal Successful! Writing result to URDF to %s' % urdf_path
bb_left_neck_tf = ros_util.matrix_to_transform(linalg.inv(new_est_cam_H_neck))
update_sensors_values_urdf(urdf_path, bb_left_neck_tf, None, None, None)
while not rospy.is_shutdown():
fcviz.update()
rospy.sleep(0.1)
