Files
Mujoco_WASM/python
Yuval Tassa 072e963fa0 Add SO3 transmission and native orientation actuator.
https://youtu.be/17XpwnqyCXs

New transmission type mjTRN_SO3: a relative orientation, targeting a ball
joint or a site+refsite pair. It is the first transmission with more than
one force output: its length is the norm of the expmap vector of the
relative rotation and its moment axes are the 3 rows of the
relative rotational Jacobian, without projecting onto per-actuator gears.

New force law mjGAIN_SO3/mjBIAS_SO3: a geodesic PD servo, force =
kp * log(q_current^-1 * q_target) - kv * velocity, exact for arbitrary axis
combinations with a unique equilibrium at every commanded orientation.
Error, moment rows and velocity all live in the child frame (joint or
site): the right-difference error is the gradient of the geodesic
potential in that frame. The parent-frame (left) error is not: driving
child-frame torques with it pumps energy at large angles, settling into
steady-spinning limit cycles (the SO3LargeAngleConvergence test). The
integrator variant stores the 3D orientation setpoint in act (actnum = 3,
re-anchored to a bounded representative at integration time). Exposed in
MJCF as <orientation joint=|site=+refsite= kp kv|dampratio>, or via
<general gaintype="so3" biastype="so3">.

The setpoint input has two charts: an expmap target (3 controls, default)
or a quaternion target (4 controls) -- <orientation input="quat">, the
first actuator with different input and output widths. The signature is
recorded in a new per-actuator field actuator_ctrlspec (mjtCtrlChart),
whose meaning is scoped by the gain type the way gain/bias parameters are;
ctrlnum is derived from it at compile time and remains the layout
authority. An explicit field rather than width inference or a prm slot:
width-as-chart cannot express same-width signatures (upcoming servo input
subsets), and prm slots are the input_mode pattern this stack retires.
The force law normalizes the commanded quaternion, making it scale- and
antipodally-invariant. The all-zero ctrl still maps to the identity via
mju_normalize4, but it is a degenerate point (a nudge of any component
commands a half-turn), so quat inputs reset to the identity quaternion:
new mj_resetCtrl sets neutral ctrl values (zero, except qw = 1), called
by mj_resetData and the viewers' Clear All. The quat chart is
restricted to dyntype 'none': integrating a quaternion setpoint linearly
is not meaningful on the manifold. New mjsActuator.ctrlspec field carries
the signature through the spec and XML round-trip.

Actuator sensors (actuatorpos/vel/frc) now report one value per force
output; dim = 3 on an SO3 actuator.

As the first actuator with nu != nactuator, this commit also makes the
viewers multi-input aware: the control sliders in simulate and studio,
which indexed per-actuator arrays by control index (out of bounds on
this model class), are generated per control and labeled with the
actuator name plus an input suffix ("orient/qw"), via the new
introspection helper mj_actuatorInputName -- the single source of truth
for input names, extended by each new multi-input type (quaternion
components are w-first: qw, qx, qy, qz). Slider ranges now honor a
defined ctrlrange even when ctrllimited is false: range is the UI hint,
limited is the clamp -- wrapped and expmap setpoints are unbounded but
still want finite sliders, while quat components are truly bounded.

The rotational demo model is orientation.xml under
test/engine/testdata/actuation/, upgraded to a three-way contrast:
per-axis wrapped servos vs an expmap-commanded vs a quat-commanded
orientation actuator, on identical checker-textured boxes. It is loaded
by the mixed-axis contrast and input-name tests, and doubles as the
viewer test model (slider groups of 3 independent, 3 grouped, 4 grouped).

PiperOrigin-RevId: 951607063
Change-Id: If235dba8e2f2ca72672e7c62531a27e967c6a373
2026-07-21 11:36:13 -07:00
..
2024-07-01 12:05:50 -07:00

MuJoCo Python Bindings

PyPI Python Version PyPI version

This package is the canonical Python bindings for the MuJoCo physics engine. These bindings are developed and maintained by Google DeepMind, and is kept up-to-date with the latest developments in MuJoCo itself.

The mujoco package provides direct access to raw MuJoCo C API functions, structs, constants, and enumerations. Structs are provided as Python classes, with Pythonic initialization and deletion semantics.

It is not the aim of this package to provide fully fledged scene/environment/game authoring API, as there are already a number of existing packages that do this well. However, this package does provide a number of lower-level components outside of MuJoCo itself that are likely to be useful to most users who access MuJoCo through Python. For example, the egl, glfw, and osmesa subpackages contain utilities for setting up OpenGL rendering contexts.

Installation

The recommended way to install this package is via PyPI:

pip install mujoco

A copy of the MuJoCo library is provided as part of the package and does not need to be downloaded or installed separately.

Source

IMPORTANT: Building from source is only necessary if you are modifying the Python bindings (or are trying to run on exceptionally old Linux systems). If that's not the case, then we recommend installing the prebuilt binaries from PyPI.

If you need to build the Python bindings from source, please consult the documentation.

Usage

Once installed, the package can be imported via import mujoco. Please consult our documentation for further detail on the package's API.

We recommend going through the tutorial notebook which covers the basics of MuJoCo using Python: Open In Colab

Versioning

The major.minor.micro portion of the version number matches the version of MuJoCo that the bindings provide. Optionally, if we release updates to the Python bindings themselves that target the same version of MuJoCo, a .postN suffix is added, for example 2.1.2.post2 represents the second update to the bindings for MuJoCo 2.1.2.

License and Disclaimer

Copyright 2022 DeepMind Technologies Limited

MuJoCo and its Python bindings are licensed under the Apache License, Version 2.0. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0.

This is not an officially supported Google product.