def get_random_maps_squeeze_between_obstacle_in_corridor_on_path():
"""
Download (or read from cache) randomly edited real world map with of a robot
in a corridor with 3 square obstacles
:return: a tuple of 3 elements
- original realworld costmap of the corridor with 3 boxes
- reference path that human took
- tuple of 1000 randomized maps that were obstained by cutting and pasting 3 boxes randomly around
their original localization
"""
key = '413293a9-086b-46e0-83ef-bb09d23c70d5'
test_maps_cache = 'test_random_maps_%s.pkl' % key
session_tar_key = 'tdwa_paper_' + os.path.splitext(
test_maps_cache)[0] + '.tar.xz'
session_tar_file = get_cache_key_path(session_tar_key)
tar_contents_folder = session_tar_file + '.contents/'
if not os.path.exists(session_tar_file):
r = requests.get(
'https://s3-us-west-1.amazonaws.com/braincorp-research-public-datasets/'
+ session_tar_key)
with open(session_tar_file, 'wb') as f:
f.write(r.content)
# remove unzipped cache if redownloaded
if os.path.exists(tar_contents_folder):
shutil.rmtree(tar_contents_folder)
if not os.path.exists(tar_contents_folder):
print('Unzipping Tar file "%s"' % session_tar_file)
try:
decompress_tar_archive(session_tar_file,
tar_contents_folder,
verbose=True)
except Exception as ex:
shutil.rmtree(tar_contents_folder)
raise ex
with open(os.path.join(tar_contents_folder, test_maps_cache), 'rb') as f:
if sys.version_info > (3, 0):
original_costmap = CostMap2D.from_state(
pickle.load(f, encoding='latin1')) # pylint: disable=unexpected-keyword-arg
static_path = pickle.load(f, encoding='latin1') # pylint: disable=unexpected-keyword-arg
test_maps = tuple([
CostMap2D.from_state(s)
for s in pickle.load(f, encoding='latin1')
]) # pylint: disable=unexpected-keyword-arg
else:
original_costmap = CostMap2D.from_state(pickle.load(f))
static_path = pickle.load(f)
test_maps = tuple(
[CostMap2D.from_state(s) for s in pickle.load(f)])
return original_costmap, static_path, test_maps
def deserialize(cls, state):
ver = state.pop('version')
assert ver == cls.VERSION
state['costmap'] = CostMap2D.from_state(state['costmap'])
reward_provider_state_instance = create_reward_provider_state(
state.pop('reward_provider_state_name'))
state[
'reward_provider_state'] = reward_provider_state_instance.deserialize(
state['reward_provider_state'])
# prepare for robot state deserialization
robot_instance = create_standard_robot(state.pop('robot_type_name'))
robot_state_type = robot_instance.get_state_type()
# deserialize the robot state
state['robot_state'] = robot_state_type.deserialize(
state['robot_state'])
# deserialize robot state queue
acc = []
for item in state['robot_state_queue']:
acc.append(robot_state_type.deserialize(item))
state['robot_state_queue'] = acc
return cls(**state)
def deserialize(cls, state):
ver = state.pop('version')
assert ver == cls.VERSION
state['costmap'] = CostMap2D.from_state(state['costmap'])
robot_instance = create_standard_robot(state.pop('robot_type_name'))
robot_state_type = robot_instance.get_state_type()
# deserialize the robot state
state['robot_state'] = robot_state_type.deserialize(
state['robot_state'])
return cls(**state)
def deserialize(cls, state):
ver = state.pop('version')
assert ver == cls.VERSION
init_costmap = CostMap2D.from_state(state['costmap'])
init_path = state['path']
params = EnvParams.deserialize(state['params'])
state = State.deserialize(state['state'])
instance = cls(init_costmap, init_path, params)
instance.set_state(state)
return instance