def __init__(self,
maze_id=None,
maze_height=0.5,
maze_size_scaling=8,
n_bins=0,
sensor_range=3.,
sensor_span=2 * math.pi,
observe_blocks=False,
put_spin_near_agent=False,
top_down_view=False,
image_size=64,
manual_collision=False,
ant_fall=False,
evaluate=False,
num_levels=1,
*args,
**kwargs):
"""Instantiate the environment.
Parameters
----------
maze_id : str
the type of maze being simulated. Can be 'Maze', 'Push', 'Fall', or
'Block'.
maze_height : float, optional
height of the floor
maze_size_scaling : float, optional
scaling factor for the maze. Specifies the size of one block.
n_bins : int, optional
number of viable objects
sensor_range : float, optional
distance whereby objects can be perceived. Must be within the span
as well.
sensor_span : float, optional
degrees of visibility
observe_blocks : bool, optional
whether to add the movable blocks to the observations
put_spin_near_agent : bool, optional
specifies whether the agent can spin blocks
top_down_view : bool, optional
if set to True, the top-down view is provided via the observations
image_size: int
determines the width and height of the rendered image
manual_collision : bool, optional
if set to True, collisions cause the agent to return to its prior
position
ant_fall : bool
specifies whether you are using the AntFall environment. The agent
in this environment is placed on a block of height 4; the "dying"
conditions for the agent need to be accordingly offset.
evaluate : bool
whether to run an evaluation. In this case an additional goal agent
is placed in the environment for visualization purposes.
num_levels : int
number of levels in the policy. 1 refers to non-hierarchical models
"""
self._maze_id = maze_id
model_cls = self.__class__.MODEL_CLASS
if model_cls is None:
raise AssertionError("MODEL_CLASS unspecified!")
if evaluate and num_levels == 2:
xml_file = "ant.xml"
elif evaluate and num_levels == 3:
xml_file = "triple_ant.xml"
else:
xml_file = "ant.xml"
xml_path = os.path.join(MODEL_DIR, xml_file)
tree = ET.parse(xml_path)
worldbody = tree.find(".//worldbody")
self.MAZE_HEIGHT = height = maze_height
self.MAZE_SIZE_SCALING = size_scaling = maze_size_scaling
self._n_bins = n_bins
self._sensor_range = sensor_range * size_scaling
self._sensor_span = sensor_span
self._observe_blocks = observe_blocks
self._put_spin_near_agent = put_spin_near_agent
self._top_down_view = top_down_view
self._manual_collision = manual_collision
self.MAZE_STRUCTURE = structure = maze_env_utils.construct_maze(
maze_id=self._maze_id)
# Elevate the maze to allow for falling.
self.elevated = any(-1 in row for row in structure)
# Are there any movable blocks?
self.blocks = any(
any(maze_env_utils.can_move(r) for r in row) for row in structure)
torso_x, torso_y = self._find_robot()
self._init_torso_x = torso_x
self._init_torso_y = torso_y
self._init_positions = [(x - torso_x, y - torso_y)
for x, y in self._find_all_robots()]
self._xy_to_rowcol = lambda x, y: (
2 + (y + size_scaling / 2) / size_scaling, 2 +
(x + size_scaling / 2) / size_scaling)
# walls (immovable), chasms (fall), movable blocks
self.image_size = image_size
self._view = np.zeros([5, 5, 3])
height_offset = 0.
if self.elevated:
# Increase initial z-pos of ant.
height_offset = height * size_scaling
torso = tree.find(".//body[@name='torso']")
torso.set('pos', '0 0 %.2f' % (0.75 + height_offset))
if self.blocks:
# If there are movable blocks, change simulation settings to
# perform better contact detection.
default = tree.find(".//default")
default.find('.//geom').set('solimp', '.995 .995 .01')
self.movable_blocks = []
for i in range(len(structure)):
for j in range(len(structure[0])):
struct = structure[i][j]
if struct == 'r' and self._put_spin_near_agent:
struct = maze_env_utils.Move.SpinXY
if self.elevated and struct not in [-1]:
# Create elevated platform.
ET.SubElement(
worldbody,
"geom",
name="elevated_%d_%d" % (i, j),
pos="%f %f %f" %
(j * size_scaling - torso_x, i * size_scaling -
torso_y, height / 2 * size_scaling),
size="%f %f %f" %
(0.5 * size_scaling, 0.5 * size_scaling,
height / 2 * size_scaling),
type="box",
material="",
contype="1",
conaffinity="1",
rgba="0.9 0.9 0.9 1",
)
if struct == 1: # Unmovable block.
# Offset all coordinates so that robot starts at the
# origin.
ET.SubElement(
worldbody,
"geom",
name="block_%d_%d" % (i, j),
pos="%f %f %f" %
(j * size_scaling - torso_x, i * size_scaling -
torso_y, height_offset + height / 2 * size_scaling),
size="%f %f %f" %
(0.5 * size_scaling, 0.5 * size_scaling,
height / 2 * size_scaling),
type="box",
material="",
contype="1",
conaffinity="1",
rgba="{} {} 0.4 1".format(i / len(structure), j /
len(structure[0]))
if top_down_view else "0.4 0.4 0.4 1",
)
elif maze_env_utils.can_move(struct): # Movable block.
# The "falling" blocks are shrunk slightly and increased in
# mass to ensure that it can fall easily through a gap in
# the platform blocks.
name = "movable_%d_%d" % (i, j)
self.movable_blocks.append((name, struct))
falling = maze_env_utils.can_move_z(struct)
spinning = maze_env_utils.can_spin(struct)
x_offset = 0.25 * size_scaling if spinning else 0.0
y_offset = 0.0
shrink = 0.1 if spinning else 0.99 if falling else 1.0
height_shrink = 0.1 if spinning else 1.0
movable_body = ET.SubElement(
worldbody,
"body",
name=name,
pos="%f %f %f" %
(j * size_scaling - torso_x + x_offset,
i * size_scaling - torso_y + y_offset, height_offset +
height / 2 * size_scaling * height_shrink),
)
ET.SubElement(
movable_body,
"geom",
name="block_%d_%d" % (i, j),
pos="0 0 0",
size="%f %f %f" %
(0.5 * size_scaling * shrink, 0.5 * size_scaling *
shrink, height / 2 * size_scaling * height_shrink),
type="box",
material="",
mass="0.001" if falling else "0.0002",
contype="1",
conaffinity="1",
rgba="0.9 0.1 0.1 1")
if maze_env_utils.can_move_x(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="1 0 0",
damping="0.0",
limited="true" if falling else "false",
range="%f %f" %
(-size_scaling, size_scaling),
margin="0.01",
name="movable_x_%d_%d" % (i, j),
pos="0 0 0",
type="slide")
if maze_env_utils.can_move_y(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="0 1 0",
damping="0.0",
limited="true" if falling else "false",
range="%f %f" %
(-size_scaling, size_scaling),
margin="0.01",
name="movable_y_%d_%d" % (i, j),
pos="0 0 0",
type="slide")
if maze_env_utils.can_move_z(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="0 0 1",
damping="0.0",
limited="true",
range="%f 0" % (-height_offset),
margin="0.01",
name="movable_z_%d_%d" % (i, j),
pos="0 0 0",
type="slide")
if maze_env_utils.can_spin(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="0 0 1",
damping="0.0",
limited="false",
name="spinable_%d_%d" % (i, j),
pos="0 0 0",
type="ball")
torso = tree.find(".//body[@name='torso']")
geoms = torso.findall(".//geom")
for geom in geoms:
if 'name' not in geom.attrib:
raise Exception("Every geom of the torso must have a name "
"defined")
_, file_path = tempfile.mkstemp(text=True, suffix='.xml')
tree.write(file_path)
try:
self.wrapped_env = model_cls(*args,
ant_fall=ant_fall,
top_down_view=top_down_view,
file_path=file_path,
**kwargs)
except AssertionError:
# for testing purposes
pass
def get_range_sensor_obs(self):
"""Return egocentric range sensor observations of maze."""
robot_x, robot_y, robot_z = self.wrapped_env.get_body_com("torso")[:3]
ori = self.get_ori()
structure = self.MAZE_STRUCTURE
size_scaling = self.MAZE_SIZE_SCALING
height = self.MAZE_HEIGHT
segments = []
# Get line segments (corresponding to outer boundary) of each immovable
# block or drop-off.
for i in range(len(structure)):
for j in range(len(structure[0])):
if structure[i][j] in [1, -1]: # There's a wall or drop-off.
cx = j * size_scaling - self._init_torso_x
cy = i * size_scaling - self._init_torso_y
x1 = cx - 0.5 * size_scaling
x2 = cx + 0.5 * size_scaling
y1 = cy - 0.5 * size_scaling
y2 = cy + 0.5 * size_scaling
struct_segments = [
((x1, y1), (x2, y1)),
((x2, y1), (x2, y2)),
((x2, y2), (x1, y2)),
((x1, y2), (x1, y1)),
]
for seg in struct_segments:
segments.append(
dict(
segment=seg,
type=structure[i][j],
))
# Get line segments (corresponding to outer boundary) of each movable
# block within the agent's z-view.
for block_name, block_type in self.movable_blocks:
block_x, block_y, block_z = self.wrapped_env.get_body_com(
block_name)[:3]
# Block in view.
if block_z + height * size_scaling / 2 \
>= robot_z >= block_z - height * size_scaling / 2:
x1 = block_x - 0.5 * size_scaling
x2 = block_x + 0.5 * size_scaling
y1 = block_y - 0.5 * size_scaling
y2 = block_y + 0.5 * size_scaling
struct_segments = [
((x1, y1), (x2, y1)),
((x2, y1), (x2, y2)),
((x2, y2), (x1, y2)),
((x1, y2), (x1, y1)),
]
for seg in struct_segments:
segments.append(dict(
segment=seg,
type=block_type,
))
# 3 for wall, drop-off, block
sensor_readings = np.zeros((self._n_bins, 3))
for ray_idx in range(self._n_bins):
ray_ori = (ori - self._sensor_span * 0.5 + (2 * ray_idx + 1.0) /
(2 * self._n_bins) * self._sensor_span)
ray_segments = []
# Get all segments that intersect with ray.
for seg in segments:
p = maze_env_utils.ray_segment_intersect(
ray=((robot_x, robot_y), ray_ori), segment=seg["segment"])
if p is not None:
ray_segments.append(
dict(
segment=seg["segment"],
type=seg["type"],
ray_ori=ray_ori,
distance=maze_env_utils.point_distance(
p, (robot_x, robot_y)),
))
if len(ray_segments) > 0:
# Find out which segment is intersected first.
first_seg = sorted(ray_segments,
key=lambda x: x["distance"])[0]
seg_type = first_seg["type"]
idx = (
0 if seg_type == 1 else # Wall.
1 if seg_type == -1 else # Drop-off.
2 if maze_env_utils.can_move(seg_type) else # Block.
None)
if first_seg["distance"] <= self._sensor_range:
sensor_readings[ray_idx][idx] = \
(self._sensor_range - first_seg["distance"]) \
/ self._sensor_range
return sensor_readings
def __init__(self,
maze_id=None,
maze_height=0.5,
maze_size_scaling=8,
n_bins=0,
sensor_range=3.,
sensor_span=2 * math.pi,
observe_blocks=False,
put_spin_near_agent=False,
top_down_view=False,
manual_collision=False,
*args,
**kwargs):
"""Instantiate the environment.
Parameters
----------
maze_id : str
TODO
maze_height : float, optional
TODO
maze_size_scaling : float, optional
TODO
n_bins : int, optional
TODO
sensor_range : float, optional
TODO
sensor_span : float, optional
TODO
observe_blocks : bool, optional
TODO
put_spin_near_agent : bool, optional
TODO
top_down_view : bool, optional
TODO
manual_collision : bool, optional
TODO
"""
self._maze_id = maze_id
model_cls = self.__class__.MODEL_CLASS
if model_cls is None:
raise AssertionError("MODEL_CLASS unspecified!")
xml_path = os.path.join(MODEL_DIR, model_cls.FILE)
tree = ET.parse(xml_path)
worldbody = tree.find(".//worldbody")
self.MAZE_HEIGHT = height = maze_height
self.MAZE_SIZE_SCALING = size_scaling = maze_size_scaling
self._n_bins = n_bins
self._sensor_range = sensor_range * size_scaling
self._sensor_span = sensor_span
self._observe_blocks = observe_blocks
self._put_spin_near_agent = put_spin_near_agent
self._top_down_view = top_down_view
self._manual_collision = manual_collision
self.MAZE_STRUCTURE = structure = maze_env_utils.construct_maze(
maze_id=self._maze_id)
# Elevate the maze to allow for falling.
self.elevated = any(-1 in row for row in structure)
# Are there any movable blocks?
self.blocks = any(
any(maze_env_utils.can_move(r) for r in row) for row in structure)
torso_x, torso_y = self._find_robot()
self._init_torso_x = torso_x
self._init_torso_y = torso_y
self._init_positions = [(x - torso_x, y - torso_y)
for x, y in self._find_all_robots()]
self._xy_to_rowcol = lambda x, y: (
2 + (y + size_scaling / 2) / size_scaling, 2 +
(x + size_scaling / 2) / size_scaling)
# walls (immovable), chasms (fall), movable blocks
self._view = np.zeros([5, 5, 3])
height_offset = 0.
if self.elevated:
# Increase initial z-pos of ant.
height_offset = height * size_scaling
torso = tree.find(".//body[@name='torso']")
torso.set('pos', '0 0 %.2f' % (0.75 + height_offset))
if self.blocks:
# If there are movable blocks, change simulation settings to
# perform better contact detection.
default = tree.find(".//default")
default.find('.//geom').set('solimp', '.995 .995 .01')
self.movable_blocks = []
for i in range(len(structure)):
for j in range(len(structure[0])):
struct = structure[i][j]
if struct == 'r' and self._put_spin_near_agent:
struct = maze_env_utils.Move.SpinXY
if self.elevated and struct not in [-1]:
# Create elevated platform.
ET.SubElement(
worldbody,
"geom",
name="elevated_%d_%d" % (i, j),
pos="%f %f %f" %
(j * size_scaling - torso_x, i * size_scaling -
torso_y, height / 2 * size_scaling),
size="%f %f %f" %
(0.5 * size_scaling, 0.5 * size_scaling,
height / 2 * size_scaling),
type="box",
material="",
contype="1",
conaffinity="1",
rgba="0.9 0.9 0.9 1",
)
if struct == 1: # Unmovable block.
# Offset all coordinates so that robot starts at the
# origin.
ET.SubElement(
worldbody,
"geom",
name="block_%d_%d" % (i, j),
pos="%f %f %f" %
(j * size_scaling - torso_x, i * size_scaling -
torso_y, height_offset + height / 2 * size_scaling),
size="%f %f %f" %
(0.5 * size_scaling, 0.5 * size_scaling,
height / 2 * size_scaling),
type="box",
material="",
contype="1",
conaffinity="1",
rgba="0.4 0.4 0.4 1",
)
elif maze_env_utils.can_move(struct): # Movable block.
# The "falling" blocks are shrunk slightly and increased in
# mass to ensure that it can fall easily through a gap in
# the platform blocks.
name = "movable_%d_%d" % (i, j)
self.movable_blocks.append((name, struct))
falling = maze_env_utils.can_move_z(struct)
spinning = maze_env_utils.can_spin(struct)
x_offset = 0.25 * size_scaling if spinning else 0.0
y_offset = 0.0
shrink = 0.1 if spinning else 0.99 if falling else 1.0
height_shrink = 0.1 if spinning else 1.0
movable_body = ET.SubElement(
worldbody,
"body",
name=name,
pos="%f %f %f" %
(j * size_scaling - torso_x + x_offset,
i * size_scaling - torso_y + y_offset, height_offset +
height / 2 * size_scaling * height_shrink),
)
ET.SubElement(
movable_body,
"geom",
name="block_%d_%d" % (i, j),
pos="0 0 0",
size="%f %f %f" %
(0.5 * size_scaling * shrink, 0.5 * size_scaling *
shrink, height / 2 * size_scaling * height_shrink),
type="box",
material="",
mass="0.001" if falling else "0.0002",
contype="1",
conaffinity="1",
rgba="0.9 0.1 0.1 1")
if maze_env_utils.can_move_x(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="1 0 0",
damping="0.0",
limited="true" if falling else "false",
range="%f %f" %
(-size_scaling, size_scaling),
margin="0.01",
name="movable_x_%d_%d" % (i, j),
pos="0 0 0",
type="slide")
if maze_env_utils.can_move_y(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="0 1 0",
damping="0.0",
limited="true" if falling else "false",
range="%f %f" %
(-size_scaling, size_scaling),
margin="0.01",
name="movable_y_%d_%d" % (i, j),
pos="0 0 0",
type="slide")
if maze_env_utils.can_move_z(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="0 0 1",
damping="0.0",
limited="true",
range="%f 0" % (-height_offset),
margin="0.01",
name="movable_z_%d_%d" % (i, j),
pos="0 0 0",
type="slide")
if maze_env_utils.can_spin(struct):
ET.SubElement(movable_body,
"joint",
armature="0",
axis="0 0 1",
damping="0.0",
limited="false",
name="spinable_%d_%d" % (i, j),
pos="0 0 0",
type="ball")
torso = tree.find(".//body[@name='torso']")
geoms = torso.findall(".//geom")
for geom in geoms:
if 'name' not in geom.attrib:
raise Exception("Every geom of the torso must have a name "
"defined")
_, file_path = tempfile.mkstemp(text=True, suffix='.xml')
tree.write(file_path)
self.wrapped_env = model_cls(*args, file_path=file_path, **kwargs)