Hacktoberfest 2026: die Issues, die Maintainer für den Oktober markiert haben – offen und einsteigerfreundlich. Hacktoberfest-Issues durchsuchen

Initialize a flexcomp object in PyMJCF

Offen
#445 4 Kommentare 0 Reaktionen 1 zugewiesene Person Auf GitHub ansehen

@quagla arbeitet bereits daran.

Seit 08.1.2024.

Bewertung

Dieses Issue wurde noch nicht bewertet.

Beschreibung

Mujoco 3.0 introduced flexcomp object for modelling deformable obejcts.

However trying to create a Prop using

class Cloth(prop.Prop):
    """Simple cloth prop that consists of a MuJoco flexcomp."""

    def _build(self, *args, **kwargs):
        del args, kwargs
        mjcf_root = mjcf.RootElement()

        mjcf_root.extension.add('plugin', plugin="mujoco.elasticity.shell")

        # Props need to contain a body called prop_root
        mjcf_root.worldbody.add('body', name='prop_root')

        cloth_object = mjcf.from_file('cloth.xml')
        mjcf_root.attach(cloth_object)

        super()._build('cloth', mjcf_root)

Errors out as flexcomp is not recoginzed as part of schema.

I modified schema.xml(which is part of mjcf under dm_control) and after adding all the tags and attibutes that I am using in an xml such as below

<mujoco model="cloth">
    <extension>
        <plugin plugin="mujoco.elasticity.shell"/>
    </extension>

    <worldbody>
        <body name="cloth">
            <flexcomp type="grid" count="10 5 1" spacing=".025 .025 .025" mass="0.1"
                      name="cloth" radius="0.001">
                <contact condim="6" solref="0.001"/>
                <edge equality="true" damping="0.1"/>
                <plugin plugin="mujoco.elasticity.shell">
                    <config key="poisson" value="0"/>
                    <config key="thickness" value="10e-3"/>
                    <!--Units are in Pa (SI)-->
                    <config key="young" value="3e4"/>
                </plugin>
            </flexcomp>
        </body>
    </worldbody>
</mujoco>

I can get the xml to be parsed and get a Prop object. I looked at composite as an example and copied over the spec as described in mujoco XML reference.

However I cannot get the simulation to run and it fails at this line self._qp_mapper = _CartesianVelocityMapper(qp_params) in dm_robotics/moma/effectors/cartesian_6d_velocity_effector.py. The error is Process finished with exit code 139 (interrupted by signal 11:SIGSEGV) which just sounds like it crashed

I cannot understand why. The whole file which I am running is

"""Minimal working example of the dm_robotics Panda model."""
import dm_env
import numpy as np
from dm_env import specs

from dm_robotics.panda import environment
from dm_robotics.panda import parameters as params
from dm_robotics.panda import run_loop, utils

from dm_robotics.panda import arm_constants

import math
from dm_control import mjcf
from dm_robotics.moma import entity_initializer, prop
from dm_control.composer.variation import distributions, rotations


class Ball(prop.Prop):
    """Simple ball prop that consists of a MuJoco sphere geom."""

    def _build(self, *args, **kwargs):
        del args, kwargs
        mjcf_root = mjcf.RootElement()
        # Props need to contain a body called prop_root
        body = mjcf_root.worldbody.add('body', name='prop_root')
        body.add('geom',
                 type='sphere',
                 size=[0.04],
                 solref=[0.01, 0.5],
                 mass=1,
                 rgba=(1, 0, 0, 1))
        super()._build('ball', mjcf_root)


class Cloth(prop.Prop):
    """Simple cloth prop that consists of a MuJoco flexcomp."""

    def _build(self, *args, **kwargs):
        del args, kwargs
        mjcf_root = mjcf.RootElement()

        mjcf_root.extension.add('plugin', plugin="mujoco.elasticity.shell")

        # Props need to contain a body called prop_root
        mjcf_root.worldbody.add('body', name='prop_root')

        cloth_object = mjcf.from_file('cloth.xml')
        mjcf_root.attach(cloth_object)

        super()._build('cloth', mjcf_root)


class Agent:
    """The agent produces a trajectory tracing the path of an eight
    in the x/y control frame of the robot using end-effector velocities.
    """

    def __init__(self, spec: specs.BoundedArray) -> None:
        self._spec = spec

    def step(self, timestep: dm_env.TimeStep) -> np.ndarray:
        """Computes velocities in the x/y plane parameterized in time."""
        time = timestep.observation['time'][0]
        r = 0.1
        vel_x = r * math.cos(time)  # Derivative of x = sin(t)
        vel_y = r * ((math.cos(time) * math.cos(time)) -
                     (math.sin(time) * math.sin(time)))
        action = np.zeros(shape=self._spec.shape, dtype=self._spec.dtype)
        # The action space of the Cartesian 6D effector corresponds
        # to the linear and angular velocities in x, y and z directions
        # respectively
        action[0] = vel_x
        action[1] = vel_y
        return action


if __name__ == '__main__':
    # We initialize the default configuration for logging
    # and argument parsing. These steps are optional.
    utils.init_logging()
    parser = utils.default_arg_parser()
    args = parser.parse_args()

    # Use RobotParams to customize Panda robots added to the environment.
    robot_params = params.RobotParams(robot_ip=args.robot_ip, actuation=arm_constants.Actuation.CARTESIAN_VELOCITY)
    panda_env = environment.PandaEnvironment(robot_params)

    ball = Ball()
    cloth = Cloth()
    props = [ball, cloth]

    panda_env.add_props(props)
    initialize_props = entity_initializer.prop_initializer.PropPlacer(
        props,
        position=distributions.Uniform(-.5, .5),
        quaternion=rotations.UniformQuaternion())

    panda_env.add_entity_initializers([initialize_props])

    with panda_env.build_task_environment() as env:
        # Print the full action, observation and reward specification
        utils.full_spec(env)
        # Initialize the agent
        agent = Agent(env.action_spec())
        # Run the environment and agent either in headless mode or inside the GUI.
        if args.gui:
            app = utils.ApplicationWithPlot()
            app.launch(env, policy=agent.step)
        else:
            run_loop.run(env, agent, [], max_steps=1000, real_time=True)

Which is just a modification of the basic example in [dm_robotics_panda] (https://github.com/JeanElsner/dm_robotics_panda)

Commenting out creating of Cloth and adding to props list works fine.

Vorherrschende Sprache
Python
Sterne
4.7k
Forks
765
Keine gemergten PRs in 30 T.

Beitragsleitfaden

Beitragsleitfaden öffnen

Erste Schritte

  1. Lesen Sie das ganze Issue und danach den Beitragsleitfaden des Projekts.
  2. Schreiben Sie ins Issue, dass Sie es übernehmen — das erspart doppelte Arbeit.
  3. Forken Sie das Repository und arbeiten Sie in einem Branch.
  4. Öffnen Sie einen Pull Request, der die Issue-Nummer nennt.

Mehr aus google-deepmind/dm_control

Alle Issues in google-deepmind/dm_control

Ähnliche Issues

Weitere Issues zu Python

Neue Issues direkt in Ihr Postfach

Eine kurze Übersicht über anfängerfreundliche GitHub-Issues.