unilab.envs.mdp.actions.actions.JointEffortAction¶
- class unilab.envs.mdp.actions.actions.JointEffortAction[source]¶
Bases:
BaseActionControl joints via effort targets.
- Parameters:
cfg (
BaseActionCfg)env (
ManagerBasedRlEnv)
Methods
__init__(cfg, env)process_actions(actions)Fail closed on the latest action-slice finite verdict.
reset([env_ids])Zero the raw actions of the selected envs.
Publish the manager-owned raw-action finite verdict.
Attributes
Whether
apply_actionsneeds state produced by the previous physics substep.Whether
apply_actionsconsumes the current packed tensor state packet.- __init__(cfg, env)¶
- Parameters:
cfg (
BaseActionCfg)env (
ManagerBasedRlEnv)
- publish_validation_verdict()¶
Fail closed on the latest action-slice finite verdict.
- Return type:
-
requires_substep_state_feedback:
ClassVar[bool] = False¶ Whether
apply_actionsneeds state produced by the previous physics substep.Falsedeclares that the generated control is invariant across all physics substeps in one control step, so the env may apply it once before a batched backend step. State-feedback terms must override this declaration withTrue.
- reset(env_ids=None)¶
Zero the raw actions of the selected envs.
-
uses_tensor_state_packet:
ClassVar[bool] = False¶ Whether
apply_actionsconsumes the current packed tensor state packet.
-
cfg:
BaseActionCfg¶