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unilab.envs.mdp.actions.actions.JointEffortActionCfg

class unilab.envs.mdp.actions.actions.JointEffortActionCfg

Bases: BaseActionCfg

Configuration for joint effort (torque) control.

Parameters:

• entity_name (str)

• clip (dict[str, tuple] | None)

• actuator_names (tuple[str, ...] | list[str])

• scale (float | dict[str, float])

• offset (float | dict[str, float])

• preserve_order (bool)

Methods

__init__(*, entity_name[, clip, scale, ...])
build(env)	Build the action term from this config.

Attributes

clip	Optional clipping bounds applied to processed actions (after scale and offset).
offset
preserve_order
scale
actuator_names
entity_name	Name of the entity in the scene that this action term controls.

build(env)

Build the action term from this config.

Parameters:

env (ManagerBasedRlEnv)

Return type:

JointEffortAction

__init__(*, entity_name, clip=None, actuator_names, scale=1.0, offset=0.0, preserve_order=False)

Parameters:

• entity_name (str)

• clip (dict[str, tuple] | None)

• actuator_names (tuple[str, ...] | list[str])

• scale (float | dict[str, float])

• offset (float | dict[str, float])

• preserve_order (bool)

clip: dict[str, tuple] | None = None

Optional clipping bounds applied to processed actions (after scale and offset). Dict maps actuator name regex patterns to (min, max) tuples, resolved the same way as scale and offset.

offset: float | dict[str, float] = 0.0

preserve_order: bool = False

scale: float | dict[str, float] = 1.0

actuator_names: tuple[str, ...] | list[str]

entity_name: str

Name of the entity in the scene that this action term controls.