sac_ae_if/local_dm_control_suite/swimmer.py
2023-05-16 12:40:47 +02:00

216 lines
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Python
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# Copyright 2017 The dm_control Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ============================================================================
"""Procedurally generated Swimmer domain."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
from dm_control import mujoco
from dm_control.rl import control
from local_dm_control_suite import base
from local_dm_control_suite import common
from dm_control.suite.utils import randomizers
from dm_control.utils import containers
from dm_control.utils import rewards
from lxml import etree
import numpy as np
from six.moves import range
_DEFAULT_TIME_LIMIT = 30
_CONTROL_TIMESTEP = .03 # (Seconds)
SUITE = containers.TaggedTasks()
def get_model_and_assets(n_joints):
"""Returns a tuple containing the model XML string and a dict of assets.
Args:
n_joints: An integer specifying the number of joints in the swimmer.
Returns:
A tuple `(model_xml_string, assets)`, where `assets` is a dict consisting of
`{filename: contents_string}` pairs.
"""
return _make_model(n_joints), common.ASSETS
@SUITE.add('benchmarking')
def swimmer6(time_limit=_DEFAULT_TIME_LIMIT, random=None,
environment_kwargs=None):
"""Returns a 6-link swimmer."""
return _make_swimmer(6, time_limit, random=random,
environment_kwargs=environment_kwargs)
@SUITE.add('benchmarking')
def swimmer15(time_limit=_DEFAULT_TIME_LIMIT, random=None,
environment_kwargs=None):
"""Returns a 15-link swimmer."""
return _make_swimmer(15, time_limit, random=random,
environment_kwargs=environment_kwargs)
def swimmer(n_links=3, time_limit=_DEFAULT_TIME_LIMIT,
random=None, environment_kwargs=None):
"""Returns a swimmer with n links."""
return _make_swimmer(n_links, time_limit, random=random,
environment_kwargs=environment_kwargs)
def _make_swimmer(n_joints, time_limit=_DEFAULT_TIME_LIMIT, random=None,
environment_kwargs=None):
"""Returns a swimmer control environment."""
model_string, assets = get_model_and_assets(n_joints)
physics = Physics.from_xml_string(model_string, assets=assets)
task = Swimmer(random=random)
environment_kwargs = environment_kwargs or {}
return control.Environment(
physics, task, time_limit=time_limit, control_timestep=_CONTROL_TIMESTEP,
**environment_kwargs)
def _make_model(n_bodies):
"""Generates an xml string defining a swimmer with `n_bodies` bodies."""
if n_bodies < 3:
raise ValueError('At least 3 bodies required. Received {}'.format(n_bodies))
mjcf = etree.fromstring(common.read_model('swimmer.xml'))
head_body = mjcf.find('./worldbody/body')
actuator = etree.SubElement(mjcf, 'actuator')
sensor = etree.SubElement(mjcf, 'sensor')
parent = head_body
for body_index in range(n_bodies - 1):
site_name = 'site_{}'.format(body_index)
child = _make_body(body_index=body_index)
child.append(etree.Element('site', name=site_name))
joint_name = 'joint_{}'.format(body_index)
joint_limit = 360.0/n_bodies
joint_range = '{} {}'.format(-joint_limit, joint_limit)
child.append(etree.Element('joint', {'name': joint_name,
'range': joint_range}))
motor_name = 'motor_{}'.format(body_index)
actuator.append(etree.Element('motor', name=motor_name, joint=joint_name))
velocimeter_name = 'velocimeter_{}'.format(body_index)
sensor.append(etree.Element('velocimeter', name=velocimeter_name,
site=site_name))
gyro_name = 'gyro_{}'.format(body_index)
sensor.append(etree.Element('gyro', name=gyro_name, site=site_name))
parent.append(child)
parent = child
# Move tracking cameras further away from the swimmer according to its length.
cameras = mjcf.findall('./worldbody/body/camera')
scale = n_bodies / 6.0
for cam in cameras:
if cam.get('mode') == 'trackcom':
old_pos = cam.get('pos').split(' ')
new_pos = ' '.join([str(float(dim) * scale) for dim in old_pos])
cam.set('pos', new_pos)
return etree.tostring(mjcf, pretty_print=True)
def _make_body(body_index):
"""Generates an xml string defining a single physical body."""
body_name = 'segment_{}'.format(body_index)
visual_name = 'visual_{}'.format(body_index)
inertial_name = 'inertial_{}'.format(body_index)
body = etree.Element('body', name=body_name)
body.set('pos', '0 .1 0')
etree.SubElement(body, 'geom', {'class': 'visual', 'name': visual_name})
etree.SubElement(body, 'geom', {'class': 'inertial', 'name': inertial_name})
return body
class Physics(mujoco.Physics):
"""Physics simulation with additional features for the swimmer domain."""
def nose_to_target(self):
"""Returns a vector from nose to target in local coordinate of the head."""
nose_to_target = (self.named.data.geom_xpos['target'] -
self.named.data.geom_xpos['nose'])
head_orientation = self.named.data.xmat['head'].reshape(3, 3)
return nose_to_target.dot(head_orientation)[:2]
def nose_to_target_dist(self):
"""Returns the distance from the nose to the target."""
return np.linalg.norm(self.nose_to_target())
def body_velocities(self):
"""Returns local body velocities: x,y linear, z rotational."""
xvel_local = self.data.sensordata[12:].reshape((-1, 6))
vx_vy_wz = [0, 1, 5] # Indices for linear x,y vels and rotational z vel.
return xvel_local[:, vx_vy_wz].ravel()
def joints(self):
"""Returns all internal joint angles (excluding root joints)."""
return self.data.qpos[3:].copy()
class Swimmer(base.Task):
"""A swimmer `Task` to reach the target or just swim."""
def __init__(self, random=None):
"""Initializes an instance of `Swimmer`.
Args:
random: Optional, either a `numpy.random.RandomState` instance, an
integer seed for creating a new `RandomState`, or None to select a seed
automatically (default).
"""
super(Swimmer, self).__init__(random=random)
def initialize_episode(self, physics):
"""Sets the state of the environment at the start of each episode.
Initializes the swimmer orientation to [-pi, pi) and the relative joint
angle of each joint uniformly within its range.
Args:
physics: An instance of `Physics`.
"""
# Random joint angles:
randomizers.randomize_limited_and_rotational_joints(physics, self.random)
# Random target position.
close_target = self.random.rand() < .2 # Probability of a close target.
target_box = .3 if close_target else 2
xpos, ypos = self.random.uniform(-target_box, target_box, size=2)
physics.named.model.geom_pos['target', 'x'] = xpos
physics.named.model.geom_pos['target', 'y'] = ypos
physics.named.model.light_pos['target_light', 'x'] = xpos
physics.named.model.light_pos['target_light', 'y'] = ypos
super(Swimmer, self).initialize_episode(physics)
def get_observation(self, physics):
"""Returns an observation of joint angles, body velocities and target."""
obs = collections.OrderedDict()
obs['joints'] = physics.joints()
obs['to_target'] = physics.nose_to_target()
obs['body_velocities'] = physics.body_velocities()
return obs
def get_reward(self, physics):
"""Returns a smooth reward."""
target_size = physics.named.model.geom_size['target', 0]
return rewards.tolerance(physics.nose_to_target_dist(),
bounds=(0, target_size),
margin=5*target_size,
sigmoid='long_tail')