def cmu_humanoid_tracking(random_state=None):
"""Requires a CMU humanoid to run down a corridor obstructed by walls."""
# Use a position-controlled CMU humanoid walker.
walker_type = cmu_humanoid.CMUHumanoidPositionControlledV2020
# Build an empty arena.
arena = arenas.Floor()
# Build a task that rewards the agent for tracking motion capture reference
# data.
task = tracking.MultiClipMocapTracking(
walker=walker_type,
arena=arena,
ref_path=cmu_mocap_data.get_path_for_cmu_2020(),
dataset='walk_tiny',
ref_steps=(1, 2, 3, 4, 5),
min_steps=10,
reward_type='comic',
)
return composer.Environment(time_limit=30,
task=task,
random_state=random_state,
strip_singleton_obs_buffer_dim=True)
def setUp(self):
super().setUp()
self.walker = walkers.CMUHumanoidPositionControlled
def _make_wrong_walker(name):
return walkers.CMUHumanoidPositionControlled(
include_face=False, model_version='2020', scale_default=True,
name=name)
self.wrong_walker = _make_wrong_walker
self.arena = arenas.Floor()
self.test_data = resources.GetResourceFilename(TEST_FILE_PATH)
def mocap_playback_env(random_state=None):
"""Constructs mocap playback environment."""
# Use a position-controlled CMU humanoid walker.
walker_type = walkers.CMUHumanoidPositionControlledV2020
# Build an empty arena.
arena = arenas.Floor()
# Build a task that rewards the agent for tracking motion capture reference
# data.
task = tracking.PlaybackTask(
walker=walker_type,
arena=arena,
ref_path=cmu_mocap_data.get_path_for_cmu(version='2020'),
dataset='run_jump_tiny',
)
return composer.Environment(time_limit=30,
task=task,
random_state=random_state,
strip_singleton_obs_buffer_dim=True)