def __init__(
self,
n_bins=20,
sensor_range=10.,
sensor_span=math.pi,
maze_id=0,
length=1,
maze_height=0.5,
maze_size_scaling=4,
coef_inner_rew=0., # a coef of 0 gives no reward to the maze from the wrapped env.
goal_rew=1000., # reward obtained when reaching the goal
death_reward=0.,
random_start=False,
direct_goal=False,
velocity_field=True,
visualize_goal=False,
*args,
**kwargs):
Serializable.quick_init(self, locals())
self._n_bins = n_bins
self._sensor_range = sensor_range
self._sensor_span = sensor_span
self._maze_id = maze_id
self.length = length
self.coef_inner_rew = coef_inner_rew
self.goal_rew = goal_rew
self.death_reward = death_reward
self.direct_goal = direct_goal
self.velocity_field = velocity_field
self.algo = None # will be added in set_algo!
self.visualize_goal = visualize_goal
model_cls = self.__class__.MODEL_CLASS
# print("model_cls", model_cls)
if model_cls is None:
raise "MODEL_CLASS unspecified!"
xml_path = osp.join(MODEL_DIR, model_cls.FILE)
# print("xml_path", xml_path)
self.tree = tree = ET.parse(xml_path)
self.worldbody = worldbody = tree.find(".//worldbody")
self.MAZE_HEIGHT = height = maze_height
self.MAZE_SIZE_SCALING = size_scaling = maze_size_scaling
self.init_actual_x = self.init_actual_y = 0
self.random_start = random_start
if self.random_start: # in kwargs
# define: actual coordinates: origin at center of struct (3, 1)
# define: mujoco coordinates: origin at the first ant
self.pool, self.p, structure, x_relative, y_relative \
= construct_maze_random(maze_id=self._maze_id, length=self.length)
# x, y_relative: x, y index in struct, relative to (3, 1)
self.MAZE_STRUCTURE = structure
self.init_actual_x = y_relative * self.MAZE_SIZE_SCALING # map x direction is list y direction!
self.init_actual_y = x_relative * self.MAZE_SIZE_SCALING
# print('self init:', self.init_actual_x, self.init_actual_y)
self.x_r_prev, self.y_r_prev = x_relative + 3, y_relative + 1 # maintain the previous map for later update
for i, tmp_line in enumerate(structure):
for j, tmp_member in enumerate(tmp_line):
if tmp_member == 'g':
self.x_g_prev, self.y_g_prev = i, j
break
# self.x_g_prev, self.y_g_prev = 3, 3 # hard code here! - (1, j) in big maze structure in maze_env_utils.py
self.x_g, self.y_g = self.x_g_prev, self.y_g_prev
else:
self.x_r_prev, self.y_r_prev = 3, 1
self.x_g_prev, self.y_g_prev = 1, 1
self.MAZE_STRUCTURE = structure = construct_maze(
maze_id=self._maze_id, length=self.length)
self.tot = 0
torso_x, torso_y = self._find_robot()
self._init_torso_x = torso_x # this is not the actual init x, just convenient for goal pos computing
self._init_torso_y = torso_y # torso pos in index coords!
self.init_torso_x = self._init_torso_x # make visible from outside
self.init_torso_y = self._init_torso_y
for i in range(len(structure)):
for j in range(len(structure[0])):
if str(structure[i][j]) == '1':
# 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 / 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")
if self.visualize_goal and str(
structure[i][j]
) == 'g': # visualize goal! uncomment this block when testing!
# offset all coordinates so that robot starts at the origin
self.goal_element =\
ET.SubElement(
self.worldbody, "geom",
name="block_%d_%d" % (i, j),
pos="%f %f %f" % (j * size_scaling - self._init_torso_x,
i * size_scaling - self._init_torso_y,
self.MAZE_HEIGHT / 2 * size_scaling),
size="%f %f %f" % (0.2 * size_scaling,
0.2 * size_scaling,
self.MAZE_HEIGHT / 2 * size_scaling),
type="box",
material="",
contype="1",
conaffinity="1",
rgba="1.0 0.0 0.0 0.5"
)
self.args = args
self.kwargs = kwargs
torso = tree.find(".//body[@name='torso']")
geoms = torso.findall(".//geom")
for geom in geoms:
# print("geom", geom.attrib)
if 'name' not in geom.attrib:
raise Exception("Every geom of the torso must have a name "
"defined")
if self.__class__.MAZE_MAKE_CONTACTS:
contact = ET.SubElement(tree.find("."), "contact")
for i in range(len(structure)):
for j in range(len(structure[0])):
if str(structure[i][j]) == '1':
for geom in geoms:
ET.SubElement(contact,
"pair",
geom1=geom.attrib["name"],
geom2="block_%d_%d" % (i, j))
_, file_path = tempfile.mkstemp(text=True)
tree.write(
file_path
) # here we write a temporal file with the robot specifications. Why not the original one??
self._goal_range = self._find_goal_range()
self.goal = np.array([(self._goal_range[0] + self._goal_range[1]) / 2,
(self._goal_range[2] + self._goal_range[3]) / 2])
# print ("goal_range", self._goal_range)
# print("x_y", self.wrapped_env.model.data.qpos.flat[0:2])
# print("goal", self.goal)
self._cached_segments = None
self.gradient_pool = [
(1, 0), (0.707, 0.707), (0, 1), (-0.707, 0.707), (-1, 0),
(-0.707, -0.707), (0, -1), (0.707, -0.707)
] # added gradient pool for train_low_with_v_gradient
inner_env = model_cls(
*args, file_path=file_path,
**kwargs) # file to the robot specifications; model_cls is AntEnv
ProxyEnv.__init__(
self, inner_env) # here is where the robot env will be initialized
def __init__(
self,
n_bins=20,
sensor_range=10.,
sensor_span=math.pi,
maze_id=0,
length=1,
maze_height=0.5,
maze_size_scaling=2,
coef_inner_rew=0., # a coef of 0 gives no reward to the maze from the wrapped env.
goal_rew=1., # reward obtained when reaching the goal
*args,
**kwargs):
Serializable.quick_init(self, locals())
Serializable.quick_init(self, locals())
self._n_bins = n_bins
self._sensor_range = sensor_range
self._sensor_span = sensor_span
self._maze_id = maze_id
self.length = length
self.coef_inner_rew = coef_inner_rew
self.goal_rew = goal_rew
model_cls = self.__class__.MODEL_CLASS
if model_cls is None:
raise "MODEL_CLASS unspecified!"
xml_path = osp.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.MAZE_STRUCTURE = structure = construct_maze(maze_id=self._maze_id,
length=self.length)
torso_x, torso_y = self._find_robot()
self._init_torso_x = torso_x
self._init_torso_y = torso_y
for i in range(len(structure)):
for j in range(len(structure[0])):
if str(structure[i][j]) == '1':
# 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 / 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")
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")
if self.__class__.MAZE_MAKE_CONTACTS:
contact = ET.SubElement(tree.find("."), "contact")
for i in range(len(structure)):
for j in range(len(structure[0])):
if str(structure[i][j]) == '1':
for geom in geoms:
ET.SubElement(contact,
"pair",
geom1=geom.attrib["name"],
geom2="block_%d_%d" % (i, j))
_, file_path = tempfile.mkstemp(text=True)
tree.write(
file_path
) # here we write a temporal file with the robot specifications. Why not the original one??
self._goal_range = self._find_goal_range()
self._cached_segments = None
inner_env = model_cls(*args, file_path=file_path,
**kwargs) # file to the robot specifications
ProxyEnv.__init__(
self, inner_env) # here is where the robot env will be initialized