def rodent_run_gaps(random_state=None):
"""Requires a rodent to run down a corridor with gaps."""
# Build a position-controlled rodent walker.
walker = rodent.Rat(
observable_options={'egocentric_camera': dict(enabled=True)})
# Build a corridor-shaped arena with gaps, where the sizes of the gaps and
# platforms are uniformly randomized.
arena = corr_arenas.GapsCorridor(platform_length=distributions.Uniform(
.4, .8),
gap_length=distributions.Uniform(.05, .2),
corridor_width=2,
corridor_length=40,
aesthetic='outdoor_natural')
# Build a task that rewards the agent for running down the corridor at a
# specific velocity.
task = corr_tasks.RunThroughCorridor(walker=walker,
arena=arena,
walker_spawn_position=(5, 0, 0),
walker_spawn_rotation=0,
target_velocity=1.0,
contact_termination=False,
terminate_at_height=-0.3,
physics_timestep=_PHYSICS_TIMESTEP,
control_timestep=_CONTROL_TIMESTEP)
return composer.Environment(time_limit=30,
task=task,
random_state=random_state,
strip_singleton_obs_buffer_dim=True)
def walker_run_gaps(random_state=None):
walker = planar_walker.PlanarWalker()
# Build a corridor-shaped arena with gaps, where the sizes of the gaps and
# platforms are uniformly randomized.
arena = corr_arenas.GapsCorridor(
platform_length=distributions.Uniform(1.25, 2.5), # (0.3, 2.5)
gap_length=distributions.Uniform(0.3, 0.7), # (0.5, 1.25)
corridor_width=10,
corridor_length=250)
# Build a task that rewards the agent for running down the corridor at a
# specific velocity.
task = corr_tasks.RunThroughCorridor(walker=walker,
arena=arena,
walker_spawn_position=(1.0, 0, 0),
stand_height=1.2,
contact_termination=False,
physics_timestep=_PHYSICS_TIMESTEP,
control_timestep=_CONTROL_TIMESTEP)
# (Chongyi Zheng): redefine reward function
task.get_reward = _walker_get_reward.__get__(task, task.get_reward)
return composer.Environment(time_limit=30,
task=task,
random_state=random_state,
strip_singleton_obs_buffer_dim=True)
def cmu_humanoid_run_gaps(random_state=None):
"""Requires a CMU humanoid to run down a corridor with gaps."""
# Build a position-controlled CMU humanoid walker.
walker = cmu_humanoid.CMUHumanoidPositionControlled(
observable_options={'egocentric_camera': dict(enabled=True)})
# Build a corridor-shaped arena with gaps, where the sizes of the gaps and
# platforms are uniformly randomized.
arena = corr_arenas.GapsCorridor(
platform_length=distributions.Uniform(.3, 2.5),
gap_length=distributions.Uniform(.5, 1.25),
corridor_width=10,
corridor_length=100)
# Build a task that rewards the agent for running down the corridor at a
# specific velocity.
task = corr_tasks.RunThroughCorridor(walker=walker,
arena=arena,
walker_spawn_position=(0.5, 0, 0),
target_velocity=3.0,
physics_timestep=0.005,
control_timestep=0.03)
return composer.Environment(time_limit=30,
task=task,
random_state=random_state,
strip_singleton_obs_buffer_dim=True)
def jumping_ball_run_gaps(random_state=None):
walker = jumping_ball.JumpingBallWithHead()
# Build a corridor-shaped arena with gaps, where the sizes of the gaps and
# platforms are uniformly randomized.
arena = corr_arenas.GapsCorridor(
platform_length=distributions.Uniform(1.0, 2.5), # (0.3, 2.5)
gap_length=distributions.Uniform(0.3, 0.7), # (0.5, 1.25)
corridor_width=10,
corridor_length=250)
# Build a task that rewards the agent for running down the corridor at a
# specific velocity.
task = corr_tasks.RunThroughCorridor(walker=walker,
arena=arena,
walker_spawn_position=(1.0, 0, 0),
target_velocity=3.0,
contact_termination=False,
physics_timestep=_PHYSICS_TIMESTEP,
control_timestep=_CONTROL_TIMESTEP)
return composer.Environment(time_limit=30,
task=task,
random_state=random_state,
strip_singleton_obs_buffer_dim=True)
