T_world = stf.SimilarityTransform3D(from_frame='world', to_frame='world')
    R_table_world = np.eye(3)
    T_table_world = stf.SimilarityTransform3D(pose=tfx.pose(R_table_world, np.zeros(3)), from_frame='world', to_frame='table')
            
    R_camera_table = np.load('data/calibration/rotation_camera_cb.npy')
    t_camera_table = np.load('data/calibration/translation_camera_cb.npy')
    cb_points_camera = np.load('data/calibration/corners_cb.npy')
    T_camera_table = stf.SimilarityTransform3D(tfx.pose(R_camera_table, t_camera_table), from_frame='table', to_frame='camera')
    T_camera_world = T_camera_table.dot(T_table_world)
    T_world_camera = T_camera_world.inverse()
    
    R_stp_obj = stable_pose.r
    T_obj_stp = stf.SimilarityTransform3D(pose=tfx.pose(R_stp_obj.T, np.zeros(3)), from_frame='stp', to_frame='obj')
            
    t_stp_table = np.array([0, 0, z])
    T_stp_table = stf.SimilarityTransform3D(pose=tfx.pose(np.eye(3), t_stp_table), from_frame='table', to_frame='stp')
    
    T_obj_world = T_obj_camera.dot(T_camera_world)
            
    # visualize the robot's understanding of the world
    logging.info('Displaying robot world state')
    mv.clf()
    mvis.MayaviVisualizer.plot_table(T_table_world, d=table_extent)
    mvis.MayaviVisualizer.plot_pose(T_world, alpha=alpha, tube_radius=tube_radius, center_scale=center_scale)
    mvis.MayaviVisualizer.plot_pose(T_obj_world, alpha=alpha, tube_radius=tube_radius, center_scale=center_scale)
    mvis.MayaviVisualizer.plot_pose(T_camera_world, alpha=alpha, tube_radius=tube_radius, center_scale=center_scale)
    mvis.MayaviVisualizer.plot_mesh(object_mesh, T_obj_world)
    mvis.MayaviVisualizer.plot_point_cloud(cb_points_camera, T_world_camera, color=(1,1,0))
    mvis.MayaviVisualizer.plot_point_cloud(points_3d, T_world_camera, color=(0,1,0), scale=0.0025)
    mv.view(focalpoint=(0,0,0))
    mv.show()