def blender_inertial_lissajous(gen_images=False):
    """Move around the asteroid in the inertial frame, but assume no rotation of the asteroid
    """
    # simulation parameters
    output_path = './visualization/blender'
    asteroid_name = 'itokawa_high'
    # create a HDF5 dataset
    hdf5_path = './data/asteroid_circumnavigate/{}_inertial_no_ast_rotation_lissajous.hdf5'.format(
        datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S"))
    dataset_name = 'landing'
    render = 'BLENDER'
    image_modulus = 1
    RelTol = 1e-6
    AbsTol = 1e-6
    ast_name = 'itokawa'
    num_faces = 64
    t0 = 0
    dt = 1
    tf = 3600 * 2
    num_steps = 3600 * 2
    loops = 2

    periodic_pos = np.array([1.495746722510590,0.000001002669660,0.006129720493607])
    periodic_vel = np.array([0.000000302161724,-0.000899607989820,-0.000000013286327])

    ast = asteroid.Asteroid(ast_name,num_faces)
    dum = dumbbell.Dumbbell(m1=500, m2=500, l=0.003)

    # instantiate the blender scene once
    camera_obj, camera, lamp_obj, lamp, itokawa_obj, scene = blender.blender_init(render_engine=render, asteroid_name=asteroid_name)

    # get some of the camera parameters
    K = blender_camera.get_calibration_matrix_K_from_blender(camera)

    # set initial state for inertial EOMs
    initial_pos = np.array([3, 3, 0]) # km for center of mass in body frame
    initial_vel = periodic_vel + attitude.hat_map(ast.omega*np.array([0,0,1])).dot(initial_pos)
    initial_R = attitude.rot3(np.pi).reshape(9) # transforms from dumbbell body frame to the inertial frame
    initial_w = np.array([0.01, 0.01, 0.01])
    initial_state = np.hstack((initial_pos, initial_vel, initial_R, initial_w))

    # instantiate ode object
    system = integrate.ode(eoms.eoms_controlled_inertial_lissajous)
    system.set_integrator('lsoda', atol=AbsTol, rtol=RelTol, nsteps=1000)
    system.set_initial_value(initial_state, t0)
    system.set_f_params(dum, ast, tf, loops)

    i_state = np.zeros((num_steps+1, 18))
    time = np.zeros(num_steps+1)
    i_state[0, :] = initial_state

    with h5py.File(hdf5_path) as image_data:
        # create a dataset
        if gen_images:
            images = image_data.create_dataset(dataset_name, (244, 537, 3, num_steps/image_modulus), dtype='uint8')
            RT_blender = image_data.create_dataset('RT', (num_steps/image_modulus, 12))
            R_i2bcam = image_data.create_dataset('R_i2bcam', (num_steps/image_modulus, 9))