[Proposal] Implement randomize_actuator_stiffness_and_dampning for explicit actuator models

[MoreTore]

Proposal

IsaacLab/source/extensions/omni.isaac.lab/omni/isaac/lab/envs/mdp/events.py

Lines 219 to 287 in a25b994

	def randomize_actuator_gains(
	env: ManagerBasedEnv,
	env_ids: torch.Tensor | None,
	asset_cfg: SceneEntityCfg,
	stiffness_distribution_params: tuple[float, float] | None = None,
	damping_distribution_params: tuple[float, float] | None = None,
	operation: Literal["add", "scale", "abs"] = "abs",
	distribution: Literal["uniform", "log_uniform", "gaussian"] = "uniform",
	):
	"""Randomize the actuator gains in an articulation by adding, scaling, or setting random values.
	This function allows randomizing the actuator stiffness and damping gains.
	The function samples random values from the given distribution parameters and applies the operation to the joint properties.
	It then sets the values into the actuator models. If the distribution parameters are not provided for a particular property,
	the function does not modify the property.
	.. tip::
	For implicit actuators, this function uses CPU tensors to assign the actuator gains into the simulation.
	In such cases, it is recommended to use this function only during the initialization of the environment.
	Raises:
	NotImplementedError: If the joint indices are in explicit motor mode. This operation is currently
	not supported for explicit actuator models.
	"""
	# extract the used quantities (to enable type-hinting)
	asset: Articulation = env.scene[asset_cfg.name]
	# resolve environment ids
	if env_ids is None:
	env_ids = torch.arange(env.scene.num_envs, device=asset.device)
	# resolve joint indices
	if asset_cfg.joint_ids == slice(None):
	joint_ids_list = range(asset.num_joints)
	joint_ids = slice(None) # for optimization purposes
	else:
	joint_ids_list = asset_cfg.joint_ids
	joint_ids = torch.tensor(asset_cfg.joint_ids, dtype=torch.int, device=asset.device)
	# check if none of the joint indices are in explicit motor mode
	for joint_index in joint_ids_list:
	for act_name, actuator in asset.actuators.items():
	# if joint indices are a slice (i.e., all joints are captured) or the joint index is in the actuator
	if actuator.joint_indices == slice(None) or joint_index in actuator.joint_indices:
	if not isinstance(actuator, ImplicitActuator):
	raise NotImplementedError(
	"Event term 'randomize_actuator_stiffness_and_damping' is performed on asset"
	f" '{asset_cfg.name}' on the joint '{asset.joint_names[joint_index]}' ('{joint_index}') which"
	f" uses an explicit actuator model '{act_name}<{actuator.__class__.__name__}>'. This operation"
	" is currently not supported for explicit actuator models."
	)
	# sample joint properties from the given ranges and set into the physics simulation
	# -- stiffness
	if stiffness_distribution_params is not None:
	stiffness = asset.data.default_joint_stiffness.to(asset.device).clone()
	stiffness = _randomize_prop_by_op(
	stiffness, stiffness_distribution_params, env_ids, joint_ids, operation=operation, distribution=distribution
	)[env_ids][:, joint_ids]
	asset.write_joint_stiffness_to_sim(stiffness, joint_ids=joint_ids, env_ids=env_ids)
	# -- damping
	if damping_distribution_params is not None:
	damping = asset.data.default_joint_damping.to(asset.device).clone()
	damping = _randomize_prop_by_op(
	damping, damping_distribution_params, env_ids, joint_ids, operation=operation, distribution=distribution
	)[env_ids][:, joint_ids]
	asset.write_joint_damping_to_sim(damping, joint_ids=joint_ids, env_ids=env_ids)

Handle the case where the actuator is explicit

[MoreTore]

I will be looking into this.