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Hi,
I'm trying to implement domain randomization on Unitree G1 robot.
To randomize actuator gains, I've added the following to '/manager_based/locomotion/velocity/config/g1/flat_env_cfg.py':
@configclass class G1Events(EventCfg): actuator_gain = EventTerm( func=mdp.randomize_actuator_gains, mode="startup", params={ "asset_cfg": SceneEntityCfg("robot", joint_names=".*"), "stiffness_distribution_params": (0., 0.), "damping_distribution_params": (0., 0.), "operation": "add", "distribution": "uniform" }, )
It is my understanding that this should NOT affect the training since I'm adding zero to actuator stiffness and damping gains.
However, when I run the training, with this added randomization, I get:
Learning iteration 243/3000 Mean reward: -10.49
Without this randomization:
Learning iteration 243/3000 Mean reward: 16.69
So, the new randomization is affecting the training somehow...I've tried this multiple times, and got the same result.
Unless this is a bug, I feel like I'm missing something
Can anyone help?
Any help would be appreciated
Regards,
Steve
The text was updated successfully, but these errors were encountered:
Hmm, after looking at events.py, I've noticed that (line 338-345):
# Randomize stiffness if stiffness_distribution_params is not None: stiffness = actuator.stiffness[env_ids].clone() stiffness[:, actuator_indices] = asset.data.default_joint_stiffness[env_ids][:, global_indices].clone() randomize(stiffness, stiffness_distribution_params) actuator.stiffness[env_ids] = stiffness if isinstance(actuator, ImplicitActuator): asset.write_joint_stiffness_to_sim(stiffness, joint_ids=actuator.joint_indices, env_ids=env_ids)
Why are we loading default_joint_stiffness before applying randomization?
It seems that this overwrites the stiffness/damping defined in the asset, thus affecting the training
Sorry, something went wrong.
Thanks for the feedback, I think it makes sense to separate the default values from the randomizations, similar to the proposal in #1416.
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Hi,
I'm trying to implement domain randomization on Unitree G1 robot.
To randomize actuator gains, I've added the following to '/manager_based/locomotion/velocity/config/g1/flat_env_cfg.py':
It is my understanding that this should NOT affect the training since I'm adding zero to actuator stiffness and damping gains.
However, when I run the training, with this added randomization, I get:
Learning iteration 243/3000
Mean reward: -10.49
Without this randomization:
Learning iteration 243/3000
Mean reward: 16.69
So, the new randomization is affecting the training somehow...I've tried this multiple times, and got the same result.
Unless this is a bug, I feel like I'm missing something
Can anyone help?
Any help would be appreciated
Regards,
Steve
The text was updated successfully, but these errors were encountered: