lerobot/lerobot/configs/env/so100_real.yaml

51 lines
1.6 KiB
YAML

# @package _global_
fps: 10
env:
name: real_world
task: null
state_dim: 15
action_dim: 3
fps: ${fps}
device: mps
wrapper:
crop_params_dict:
observation.images.front: [171, 207, 116, 251]
observation.images.side: [232, 200, 142, 204]
resize_size: [128, 128]
control_time_s: 10
reset_follower_pos: false
use_relative_joint_positions: true
reset_time_s: 5
display_cameras: false
delta_action: null #0.3
joint_masking_action_space: null #[1, 1, 1, 1, 0, 0] # disable wrist and gripper
add_joint_velocity_to_observation: true
add_ee_pose_to_observation: true
# If null then the teleoperation will be used to reset the robot
# Bounds for pushcube_gamepad_lerobot15 dataset and experiments
# fixed_reset_joint_positions: [-19.86, 103.19, 117.33, 42.7, 13.89, 0.297]
# ee_action_space_params: # If null then ee_action_space is not used
# bounds:
# max: [0.291, 0.147, 0.074]
# min: [0.139, -0.143, 0.03]
# Bounds for insertcube_gamepad dataset and experiments
fixed_reset_joint_positions: [20.0, 90., 90., 75., -0.7910156, -0.5673759]
ee_action_space_params:
bounds:
max: [0.25295413, 0.07498981, 0.06862044]
min: [0.2010096, -0.12, 0.0433196]
use_gamepad: true
x_step_size: 0.03
y_step_size: 0.03
z_step_size: 0.03
reward_classifier:
pretrained_path: null # outputs/classifier/13-02-random-sample-resnet10-frozen/checkpoints/best/pretrained_model
config_path: null # lerobot/configs/policy/hilserl_classifier.yaml