PositionActionManager#

class genesis_forge.managers.action.PositionActionManager(env: GenesisEnv, actuator_manager: ActuatorManager | None = None, scale: float | dict[str, float] = 1.0, offset: float | dict[str, float] = 0.0, clip: tuple[float, float] | dict[str, tuple[float, float]] = None, use_default_offset: bool = True, action_handler: Callable[[torch.Tensor], None] = None, quiet_action_errors: bool = False, delay_step: int = 0, **kwargs)[source]#

Bases: BaseActionManager

Converts actions to DOF positions, using affine transformations (scale and offset).

\[position = offset + scaling * action\]

If use_default_offset is True, the offset will be set to the default_pos value for each DOF/joint.

Parameters:

env – The environment to manage the DOF actuators for.
actuator_manager – The actuator manager which is used to setup and control the DOF joints.
scale – How much to scale the action.
offset – Offset factor for the action.
use_default_offset – Whether to use default joint positions configured in the articulation asset as offset. Defaults to True.
clip – Clip the action values to the range. If omitted, the action values will automatically be clipped to the joint limits.
quiet_action_errors – Whether to quiet action errors.
delay_step – The number of steps to delay the actions for. This is an easy way to emulate the latency in the system.

Example:

class MyEnv(ManagedEnvironment):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # ...define scene and robot...

    def config(self):
        self.actuator_manager = ActuatorManager(
            self,
            joint_names=".*",
            default_pos={".*": 0.0},
            kp=50,
            kv=0.5,
            max_force=8.0,
        )
        self.action_manager = PositionActionManager(
            self,
            scale=0.5,
            use_default_offset=True,
            actuator_manager=self.actuator_manager,
        )

Example using the manager directly:

class MyEnv(GenesisEnv):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # ...define scene and robot...

        self.actuator_manager = ActuatorManager(
            self,
            joint_names=".*",
            default_pos={".*": 0.0},
            kp=50,
            kv=0.5,
            max_force=8.0,
        )
        self.action_manager = PositionActionManager(
            self,
            scale=0.5,
            offset=0.0,
            use_default_offset=True,
        )

    def build(self):
        super().build()
        self.actuator_manager.build()
        self.action_manager.build()

    step(self, actions: torch.Tensor) -> None:
        super().step(actions)
        self.action_manager.step(actions)

        # ...do other step things...

    reset(self, envs_idx: list[int] = None) -> None:
        super().reset(envs_idx)
        self.actuator_manager.reset(envs_idx)
        self.action_manager.reset(envs_idx)

        # ...do other reset things...

build()[source]#: Builds the manager and initialized all the buffers.

get_actions() → torch.Tensor#: Get the current actions for the environments.

get_dofs_force(noise: float = 0.0, clip_to_max_force: bool = False)[source]#

Deprecated: Use the actuator manager directly.

Return the force experienced by the enabled DOFs. This is a wrapper for RigidEntity.get_dofs_force.

Parameters:

noise – The maximum amount of random noise to add to the force values returned.
clip_to_max_force – Clip the force returned to the maximum force defined by the max_force parameter.

Returns:

The force experienced by the enabled DOFs.

get_dofs_position(noise: float = 0.0)[source]#

Deprecated: Use the actuator manager directly.

Return the current position of the enabled DOFs. This is a wrapper for RigidEntity.get_dofs_position.

Parameters:: noise – The maximum amount of random noise to add to the position values returned.

get_dofs_velocity(noise: float = 0.0, clip: tuple[float, float] = None)[source]#

Deprecated: Use the actuator manager directly.

Return the current velocity of the enabled DOFs. This is a wrapper for RigidEntity.get_dofs_velocity.

Parameters:

noise – The maximum amount of random noise to add to the velocity values returned.
clip – Clip the velocity returned.

handle_actions(actions: torch.Tensor) → torch.Tensor[source]#

Converts the actions to position commands, and send them to the DOF actuators. Override this function if you want to change the action handling logic.

Parameters:: actions – The incoming step actions to handle.
Returns:: The processed and handled actions.

reset(envs_idx: list[int] | None)#: Reset environments.

step(actions: torch.Tensor) → torch.Tensor[source]#

Take the incoming actions for this step and handle them.

Parameters:: actions – The incoming step actions to handle.

property action_space: tuple[float, float]#: Returns the actions space for the environment, based on the number of DOFs defined in this action manager.

property actions: torch.Tensor#: The actions for for the current step.

property actuators: ActuatorManager#: Get the actuator manager.

property default_dofs_pos: torch.Tensor#: Return the default DOF positions.

property dofs_idx: list[int]#: Get the indices of the DOF that are enabled (via joint_names).

property num_actions: int#: Get the number of actions.

property raw_actions: torch.Tensor#: The actions received from the policy, before being converted.

PositionActionManager#

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