def __init__(self, args):
self.env = PepperRLEnv(args)
# Assumes merged lidar
# no direct obstacle positions
from gym.spaces.box import Box
self.observation_space = Box(
low=-100.,
high=100.,
shape=(self.env.kObsBufferSize,
self.env.kStateSize + self.env.kMergedScanSize),
dtype=np.float32,
)
VecEnv.__init__(self, self.env.n_agents(), self.observation_space,
self.env.action_space)
self.keys, shapes, dtypes = obs_space_info(self.observation_space)
self.buf_obs = OrderedDict([(k,
np.zeros(
(self.num_envs, ) + tuple(shapes[k]),
dtype=dtypes[k])) for k in self.keys])
self.buf_dones = np.zeros((self.num_envs, ), dtype=np.bool)
self.buf_rews = np.zeros((self.num_envs, ), dtype=np.float32)
self.buf_infos = [{} for _ in range(self.num_envs)]
self.actions = None
self.metadata = self.env.metadata
def __init__(self, args):
self.envs = [None for _ in range(args.n_envs)]
map2d = None
tsdf = None
for env_idx in range(args.n_envs):
self.envs[env_idx] = PepperRLEnv(args, map_=map2d, tsdf_=tsdf)
map2d = self.envs[env_idx].map2d
tsdf = self.envs[env_idx].tsdf
# Assumes merged lidar
# no direct obstacle positions
from gym.spaces.box import Box
self.observation_space = Box(
low=-100.,
high=100.,
shape=(self.envs[0].kObsBufferSize,
self.envs[0].kStateSize + self.envs[0].kMergedScanSize),
dtype=np.float32,
)
VecEnv.__init__(self, len(self.envs), self.observation_space,
self.envs[0].action_space)
self.keys, shapes, dtypes = obs_space_info(self.observation_space)
self.buf_obs = OrderedDict([(k,
np.zeros(
(self.num_envs, ) + tuple(shapes[k]),
dtype=dtypes[k])) for k in self.keys])
self.buf_dones = np.zeros((self.num_envs, ), dtype=np.bool)
self.buf_rews = np.zeros((self.num_envs, ), dtype=np.float32)
self.buf_infos = [{} for _ in range(self.num_envs)]
self.actions = None
self.metadata = [env.metadata for env in self.envs]
def __init__(self, env_fns):
self.envs = [fn() for fn in env_fns]
env = self.envs[0]
VecEnv.__init__(self, len(env_fns), env.observation_space, env.action_space)
obs_space = env.observation_space
self.keys, shapes, dtypes = obs_space_info(obs_space)
self.buf_obs = OrderedDict([
(k, np.zeros((self.num_envs,) + tuple(shapes[k]), dtype=dtypes[k]))
for k in self.keys])
self.buf_dones = np.zeros((self.num_envs,), dtype=np.bool)
self.buf_rews = np.zeros((self.num_envs,), dtype=np.float32)
self.buf_infos = [{} for _ in range(self.num_envs)]
self.actions = None
self.metadata = env.metadata
def __init__(self, *args):
self.env = MultiIARLEnv(*args)
VecEnv.__init__(self, self.env.n_envs, self.env.observation_space,
self.env.action_space)
obs_space = self.env.observation_space
self.keys, shapes, dtypes = obs_space_info(obs_space)
self.buf_obs = OrderedDict([(k,
np.zeros(
(self.num_envs, ) + tuple(shapes[k]),
dtype=dtypes[k])) for k in self.keys])
self.buf_dones = np.zeros((self.num_envs, ), dtype=np.bool)
self.buf_rews = np.zeros((self.num_envs, ), dtype=np.float32)
self.buf_infos = [{} for _ in range(self.num_envs)]
self.actions = None
self.metadata = self.env.metadata
