Principle:Google deepmind Dm control MJCF Physics Compilation
| Metadata | |
|---|---|
| Knowledge Sources | dm_control |
| Domains | Physics Simulation, Robotics, Simulation Runtime |
| Last Updated | 2026-02-15 00:00 GMT |
Overview
Compiling a declarative model definition into an executable physics simulation and providing element-level data access through bindings bridges the gap between model authoring and simulation runtime.
Description
MJCF Physics Compilation is the step that converts an in-memory MJCF model tree into a live MuJoCo physics simulation. Until compilation, the model is purely declarative: it describes what the simulation should contain but does not allocate memory, compute inertias, or prepare rendering buffers. Compilation triggers MuJoCo's internal compiler, which validates the model, infers missing quantities (e.g., body inertias from geom shapes), and produces the mjModel and mjData structures that drive simulation stepping.
The compilation step involves:
- XML generation: The MJCF object tree is serialized to an XML string with fully qualified (prefixed) identifiers. All binary assets (meshes, textures, heightfields) are collected into a dictionary.
- MuJoCo compilation: The XML and assets are passed to MuJoCo's C-level compiler, which produces the physics model and data structures.
- Binding setup: The resulting
Physicsobject maintains a binding cache that allows MJCF elements to be mapped directly to their corresponding rows in MuJoCo's data arrays.
The binding mechanism is what makes the compiled physics truly useful in a PyMJCF context. Instead of looking up array indices by string name, a user can call physics.bind(element) to obtain a Binding object. This object exposes the physics data associated with that element (positions, velocities, forces, etc.) as regular Python attributes. Writing to a binding attribute updates the underlying MuJoCo data and automatically marks the physics state as dirty, triggering lazy recalculation of derived quantities on the next read.
Bindings also support batch operations: binding a list of elements returns an object whose attributes provide array views over all of those elements simultaneously.
Usage
Physics compilation is the gateway to simulation:
- Compile a fully assembled model to run forward dynamics, inverse dynamics, or control tasks.
- Bind MJCF elements to the physics to read sensor data, joint positions, or body poses.
- Write to bindings to set joint configurations, apply forces, or modify model parameters at runtime.
- Reload the physics from a modified MJCF model without recreating the Python object.
Theoretical Basis
FUNCTION compile(mjcf_model):
xml_string = mjcf_model.to_xml_string()
assets = mjcf_model.get_assets()
physics = MuJoCo.compile(xml_string, assets)
RETURN PhysicsWrapper(physics)
FUNCTION bind(physics, mjcf_element):
namespace = element_to_namespace(mjcf_element)
named_index = mjcf_element.full_identifier
RETURN Binding(physics, namespace, named_index)
CLASS Binding:
FUNCTION __getattr__(name):
indexer = physics.named.data[name] # or model[name]
RETURN indexer[named_index] # returns array view
FUNCTION __setattr__(name, value):
indexer = physics.named.data[name]
indexer[named_index] = value
IF triggers_dirty(name):
physics.mark_dirty()
The lazy recalculation strategy ensures that multiple attribute writes do not cause redundant forward dynamics computations. The physics is only brought up to date when a derived quantity is actually read.