key-data / models /embodied /envs /loconav.py
tostido's picture
Add embodied module back
faa3682
import functools
import os
import warnings
import elements
import embodied
import numpy as np
class LocoNav(embodied.Env):
DEFAULT_CAMERAS = dict(
ant=4,
quadruped=5,
)
def __init__(
self, name, repeat=1, size=(64, 64), camera=-1, again=False,
termination=False, weaker=1.0):
if name.endswith('hz'):
name, freq = name.rsplit('_', 1)
freq = int(freq.strip('hz'))
else:
freq = 50
if 'MUJOCO_GL' not in os.environ:
os.environ['MUJOCO_GL'] = 'egl'
from dm_control import composer
from dm_control.locomotion.props import target_sphere
from dm_control.locomotion.tasks import random_goal_maze
walker, arena = name.split('_', 1)
if camera == -1:
camera = self.DEFAULT_CAMERAS.get(walker, 0)
self._walker = self._make_walker(walker)
arena = self._make_arena(arena)
target = target_sphere.TargetSphere(radius=1.2, height_above_ground=0.0)
task = random_goal_maze.RepeatSingleGoalMaze(
walker=self._walker, maze_arena=arena, target=target,
max_repeats=1000 if again else 1,
randomize_spawn_rotation=True,
target_reward_scale=1.0,
aliveness_threshold=-0.5 if termination else -1.0,
contact_termination=False,
physics_timestep=min(1 / freq / 4, 0.02),
control_timestep=1 / freq)
if not again:
def after_step(self, physics, random_state):
super(random_goal_maze.RepeatSingleGoalMaze, self).after_step(
physics, random_state)
self._rewarded_this_step = self._target.activated
self._targets_obtained = int(self._target.activated)
task.after_step = functools.partial(after_step, task)
env = composer.Environment(
time_limit=60, task=task, random_state=None,
strip_singleton_obs_buffer_dim=True)
from . import dmc
self._env = dmc.DMC(env, repeat, size=size, camera=camera, image=False)
self._visited = None
self._weaker = weaker
@property
def obs_space(self):
spaces = self._env.obs_space.copy()
spaces['log/coverage'] = elements.Space(np.int32, low=-1)
return spaces
@property
def act_space(self):
return self._env.act_space
def step(self, action):
with warnings.catch_warnings():
warnings.filterwarnings('ignore', '.*is a deprecated alias for.*')
action = action.copy()
action['action'] *= self._weaker
obs = self._env.step(action)
if obs['is_first']:
self._visited = set()
global_pos = self._walker.get_pose(
self._env._dmenv._physics)[0].reshape(-1)
self._visited.add(tuple(np.round(global_pos[:2]).astype(int).tolist()))
obs['log/coverage'] = np.int32(len(self._visited))
return obs
def _make_walker(self, name):
if name == 'ant':
from dm_control.locomotion.walkers import ant
return ant.Ant()
elif name == 'quadruped':
from . import loconav_quadruped
return loconav_quadruped.Quadruped()
else:
raise NotImplementedError(name)
def _make_arena(self, name):
import labmaze
from dm_control import mjcf
from dm_control.locomotion.arenas import labmaze_textures
from dm_control.locomotion.arenas import mazes
import matplotlib.pyplot as plt
class WallTexture(labmaze_textures.WallTextures):
def _build(self, color=[0.8, 0.8, 0.8], model='labmaze_style_01'):
self._mjcf_root = mjcf.RootElement(model=model)
self._textures = [self._mjcf_root.asset.add(
'texture', type='2d', name='wall', builtin='flat',
rgb1=color, width=100, height=100)]
wall_textures = {'*': WallTexture([0.8, 0.8, 0.8])}
cmap = plt.get_cmap('tab10')
for index in range(9):
wall_textures[str(index + 1)] = WallTexture(cmap(index)[:3])
layout = ''.join([
line[::2].replace('.', ' ') + '\n' for line in MAPS[name]])
maze = labmaze.FixedMazeWithRandomGoals(
entity_layer=layout,
num_spawns=1, num_objects=1, random_state=None)
arena = mazes.MazeWithTargets(
maze, xy_scale=1.2, z_height=2.0, aesthetic='default',
wall_textures=wall_textures, name='maze')
return arena
MAPS = {
'maze_s': (
' 6 6 6 6 6',
' 6 . . . 6',
' 6 . G . 6',
' 6 . . . 6',
' 5 . . . 4',
' 5 . . . 4',
'1 1 1 1 5 5 5 . . . 4',
'1 . . . . . . . . . 3',
'1 . P . . . . . . . 3',
'1 . . . . . . . . . 3',
'1 1 1 1 2 2 2 3 3 3 3',
),
'maze_m': (
'6 6 6 6 8 8 8 7 7 7 7',
'6 . . . . . . . . . 7',
'6 . G . . . . . . . 7',
'6 . . . . . . . . . 7',
'6 6 6 5 5 5 5 . . . 4',
' 5 . . . 4',
'1 1 1 1 5 5 5 . . . 4',
'1 . . . . . . . . . 3',
'1 . P . . . . . . . 3',
'1 . . . . . . . . . 3',
'1 1 1 1 2 2 2 3 3 3 3',
),
'maze_l': (
'8 8 8 8 7 7 7 6 6 6 6 . . .',
'8 . . . . . . . . . 6 . . .',
'8 . G . . . . . . . 6 . . .',
'8 . . . . . . . . . 6 5 5 5',
'8 8 8 8 7 7 7 . . . . . . 5',
'. . . . . . 7 . . . . . . 5',
'1 1 1 1 1 . 7 . . . . . . 5',
'1 . . . 1 . 7 9 9 9 . . . 5',
'1 . . . 1 . . . . 9 . . . 5',
'1 . . . 1 1 1 9 9 9 . . . 5',
'2 . . . . . . . . . . . . 4',
'2 . . . . P . . . . . . . 4',
'2 . . . . . . . . . . . . 4',
'2 2 2 2 3 3 3 3 3 3 4 4 4 4',
),
'maze_xl': (
'9 9 9 9 9 9 9 8 8 8 8 . 4 4 4 4 4',
'9 . . . . . . . . . 8 . 4 . . . 4',
'9 . . . . . . . G . 8 . 4 . . . 4',
'9 . . . . . . . . . 8 . 4 . . . 4',
'6 . . . 7 7 7 8 8 8 8 . 5 . . . 3',
'6 . . . 7 . . . . . . . 5 . . . 3',
'6 . . . 7 7 7 5 5 5 5 5 5 . . . 3',
'5 . . . . . . . . . . . . . . . 3',
'5 . . . . . . . . . . . . . . . 3',
'5 . . . . . . . . . . . . . . . 3',
'5 5 5 5 4 4 4 . . . 6 6 6 . . . 3',
'. . . . . . 4 . . . 6 . 6 . . . 3',
'1 1 1 1 4 4 4 . . . 6 . 6 . . . 3',
'1 . . . . . . . . . 2 . 1 . . . 1',
'1 . P . . . . . . . 2 . 1 . . . 1',
'1 . . . . . . . . . 2 . 1 . . . 1',
'1 1 1 1 1 1 1 2 2 2 2 . 1 1 1 1 1',
),
'maze_xxl': (
'7 7 7 7 * * * 6 6 6 * * * 9 9 9 9',
'7 . . . . . . . . . . . . . . . 9',
'7 . . . . . . . . . . . . . G . 9',
'7 . . . . . . . . . . . . . . . 9',
'* . . . 5 5 5 * * * * * * 9 9 9 9',
'* . . . 5 . . . . . . . . . . . .',
'* . . . 5 5 5 * * * * * * 3 3 3 3',
'8 . . . . . . . . . . . . . . . 3',
'8 . . . . . . . . . . . . . . . 3',
'8 . . . . . . . . . . . . . . . 3',
'8 8 8 8 * * * * * * 4 4 4 . . . *',
'. . . . . . . . . . . . 4 . . . *',
'1 1 1 1 * * * * * * 4 4 4 . . . *',
'1 . . . . . . . . . . . . . . . 2',
'1 . P . . . . . . . . . . . . . 2',
'1 . . . . . . . . . . . . . . . 2',
'1 1 1 1 * * * 6 6 6 * * * 2 2 2 2',
),
'empty': (
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
'. . . . . . . . . . . . . . . . .',
),
}