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After collecting demonstrations in the robosuite env, and then converting them using the conversion script provided, there seems to be an issue of action not being in the scale [-1, 1] .
I have collected the demonstrations using "collect_human_demonstrations.py".
then python conversion/convert_robosuite.py
get_dataset_info.py
total transitions: 27087
total trajectories: 35
traj length mean: 773.9142857142857
traj length std: 240.8114106727588
traj length min: 362
traj length max: 1490
action min: -7.500000000000007
action max: 7.5
==== Filter Keys ====
filter key train with 32 demos
filter key valid with 3 demos
==== Dataset Structure ====
episode demo_1 with 1129 transitions
key: actions with shape (1129, 6)
key: states with shape (1129, 13)
Traceback (most recent call last):
File "get_dataset_info.py", line 134, in
raise Exception("Dataset should have actions in [-1., 1.] but got bounds [{}, {}]".format(action_min, action_max))
Exception: Dataset should have actions in [-1., 1.] but got bounds [-7.500000000000007, 7.5]
the actions not scaled down automatically
The text was updated successfully, but these errors were encountered:
I think if you clip the actions in the script it will fix the issue, this was also suggested by the authors in one of the previous issues, if I am not wrong.
What I have noticed is that, the keyboard interface is binary, and training with "keyboard-interface" collected data results in poor training. I think to overcome this, the solution is to use a "SpaceMouse" or some alternative interface.
After collecting demonstrations in the robosuite env, and then converting them using the conversion script provided, there seems to be an issue of action not being in the scale [-1, 1] .
I have collected the demonstrations using "collect_human_demonstrations.py".
then python conversion/convert_robosuite.py
get_dataset_info.py
total transitions: 27087
total trajectories: 35
traj length mean: 773.9142857142857
traj length std: 240.8114106727588
traj length min: 362
traj length max: 1490
action min: -7.500000000000007
action max: 7.5
==== Filter Keys ====
filter key train with 32 demos
filter key valid with 3 demos
==== Env Meta ====
{
"type": 1,
"env_name": "Wipe",
"env_version": "1.4.1",
"env_kwargs": {
"env_name": "Wipe",
"robots": "UR5e",
"controller_configs": {
"type": "OSC_POSE",
"input_max": 1,
"input_min": -1,
"output_max": [
0.05,
0.05,
0.05,
0.5,
0.5,
0.5
],
"output_min": [
-0.05,
-0.05,
-0.05,
-0.5,
-0.5,
-0.5
],
"kp": 150,
"damping_ratio": 1,
"impedance_mode": "fixed",
"kp_limits": [
0,
300
],
"damping_ratio_limits": [
0,
10
],
"position_limits": null,
"orientation_limits": null,
"uncouple_pos_ori": true,
"control_delta": true,
"interpolation": null,
"ramp_ratio": 0.2
}
}
}
==== Dataset Structure ====
episode demo_1 with 1129 transitions
key: actions with shape (1129, 6)
key: states with shape (1129, 13)
Traceback (most recent call last):
File "get_dataset_info.py", line 134, in
raise Exception("Dataset should have actions in [-1., 1.] but got bounds [{}, {}]".format(action_min, action_max))
Exception: Dataset should have actions in [-1., 1.] but got bounds [-7.500000000000007, 7.5]
the actions not scaled down automatically
The text was updated successfully, but these errors were encountered: