def build_laikago_env( motor_control_mode, enable_rendering):
sim_params = locomotion_gym_config.SimulationParameters()
sim_params.enable_rendering = enable_rendering
sim_params.motor_control_mode = motor_control_mode
sim_params.reset_time = 2
sim_params.num_action_repeat = 10
sim_params.enable_action_interpolation = False
sim_params.enable_action_filter = False
sim_params.enable_clip_motor_commands = False
gym_config = locomotion_gym_config.LocomotionGymConfig(simulation_parameters=sim_params)
robot_class = laikago.Laikago
sensors = [
robot_sensors.MotorAngleSensor(num_motors=laikago.NUM_MOTORS),
robot_sensors.IMUSensor(),
environment_sensors.LastActionSensor(num_actions=laikago.NUM_MOTORS)
]
task = default_task.DefaultTask()
env = locomotion_gym_env.LocomotionGymEnv(gym_config=gym_config, robot_class=robot_class,
robot_sensors=sensors, task=task)
#env = observation_dictionary_to_array_wrapper.ObservationDictionaryToArrayWrapper(env)
#env = trajectory_generator_wrapper_env.TrajectoryGeneratorWrapperEnv(env,
# trajectory_generator=simple_openloop.LaikagoPoseOffsetGenerator(action_limit=laikago.UPPER_BOUND))
return env
def build_imitation_env(motion_files, num_parallel_envs, mode,
enable_randomizer, enable_rendering, arg_enable_cycle_sync,
robot_class=laikago.Laikago,
trajectory_generator=simple_openloop.LaikagoPoseOffsetGenerator(action_limit=laikago.UPPER_BOUND)):
assert len(motion_files) > 0
curriculum_episode_length_start = 20
curriculum_episode_length_end = 600
sim_params = locomotion_gym_config.SimulationParameters()
sim_params.enable_rendering = enable_rendering
sim_params.allow_knee_contact = True
sim_params.motor_control_mode = robot_config.MotorControlMode.POSITION
gym_config = locomotion_gym_config.LocomotionGymConfig(simulation_parameters=sim_params)
sensors = [
sensor_wrappers.HistoricSensorWrapper(wrapped_sensor=robot_sensors.MotorAngleSensor(num_motors=laikago.NUM_MOTORS), num_history=3),
sensor_wrappers.HistoricSensorWrapper(wrapped_sensor=robot_sensors.IMUSensor(['R', 'P', 'Y', 'dR', 'dP', 'dY']), num_history=3), # added yaw and dYaw in IMU.
# sensor_wrappers.HistoricSensorWrapper(wrapped_sensor=robot_sensors.IMUSensor(), num_history=3), # added yaw and dYaw in IMU.
sensor_wrappers.HistoricSensorWrapper(wrapped_sensor=environment_sensors.LastActionSensor(num_actions=laikago.NUM_MOTORS), num_history=3)
]
task = imitation_task.ImitationTask(ref_motion_filenames=motion_files,
enable_cycle_sync=arg_enable_cycle_sync,
tar_frame_steps=[1, 2, 10, 30],
ref_state_init_prob=0.9,
warmup_time=0.25)
randomizers = []
if enable_randomizer:
randomizer = controllable_env_randomizer_from_config.ControllableEnvRandomizerFromConfig(verbose=False)
randomizers.append(randomizer)
env = locomotion_gym_env.LocomotionGymEnv(gym_config=gym_config, robot_class=robot_class,
env_randomizers=randomizers, robot_sensors=sensors, task=task)
env = observation_dictionary_to_array_wrapper.ObservationDictionaryToArrayWrapper(env)
env = trajectory_generator_wrapper_env.TrajectoryGeneratorWrapperEnv(env,
trajectory_generator=trajectory_generator)
if mode == "test":
curriculum_episode_length_start = curriculum_episode_length_end
env = imitation_wrapper_env.ImitationWrapperEnv(env,
episode_length_start=curriculum_episode_length_start,
episode_length_end=curriculum_episode_length_end,
curriculum_steps=30000000,
num_parallel_envs=num_parallel_envs)
return env
def build_regular_env(robot_class,
motor_control_mode,
enable_rendering=False,
on_rack=False,
action_limit=(0.75, 0.75, 0.75),
wrap_trajectory_generator=True):
sim_params = locomotion_gym_config.SimulationParameters()
sim_params.enable_rendering = enable_rendering
sim_params.motor_control_mode = motor_control_mode
sim_params.reset_time = 2
sim_params.num_action_repeat = 10
sim_params.enable_action_interpolation = False
sim_params.enable_action_filter = False
sim_params.enable_clip_motor_commands = False
sim_params.robot_on_rack = on_rack
gym_config = locomotion_gym_config.LocomotionGymConfig(
simulation_parameters=sim_params)
sensors = [
robot_sensors.BaseDisplacementSensor(),
robot_sensors.IMUSensor(),
robot_sensors.MotorAngleSensor(num_motors=a1.NUM_MOTORS),
]
task = simple_forward_task.SimpleForwardTask()
env = locomotion_gym_env.LocomotionGymEnv(gym_config=gym_config,
robot_class=robot_class,
robot_sensors=sensors,
task=task)
env = obs_dict_to_array_wrapper.ObservationDictionaryToArrayWrapper(
env)
if (motor_control_mode
== robot_config.MotorControlMode.POSITION) and wrap_trajectory_generator:
if robot_class == laikago.Laikago:
env = trajectory_generator_wrapper_env.TrajectoryGeneratorWrapperEnv(
env,
trajectory_generator=simple_openloop.LaikagoPoseOffsetGenerator(
action_limit=action_limit))
elif robot_class == a1.A1:
env = trajectory_generator_wrapper_env.TrajectoryGeneratorWrapperEnv(
env,
trajectory_generator=simple_openloop.LaikagoPoseOffsetGenerator(
action_limit=action_limit))
return env