Documentation Index
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Embodiment tags are used to identify the robot embodiment in the data. They enable cross-embodiment training by providing consistent identifiers across datasets.
Naming convention
Embodiment tags follow the pattern <dataset>_<robot_name>. If using multiple datasets with the same robot (e.g., sim GR1 and real GR1), you can drop the dataset name and use only the robot name.
EmbodimentTag
from gr00t.data.embodiment_tags import EmbodimentTag
ROBOCASA_PANDA_OMRON
The RoboCasa Panda robot with Omron mobile base.
EmbodimentTag.ROBOCASA_PANDA_OMRON
# Value: "robocasa_panda_omron"
GR1
The Fourier GR1 robot.
EmbodimentTag.GR1
# Value: "gr1"
Posttrain embodiment tags
These embodiments are pre-registered for post-training:
UNITREE_G1
The Unitree G1 robot.
EmbodimentTag.UNITREE_G1
# Value: "unitree_g1"
LIBERO_PANDA
The Libero Panda robot.
EmbodimentTag.LIBERO_PANDA
# Value: "libero_panda"
OXE_GOOGLE
The Open-X-Embodiment Google robot.
EmbodimentTag.OXE_GOOGLE
# Value: "oxe_google"
OXE_WIDOWX
The Open-X-Embodiment WidowX robot.
EmbodimentTag.OXE_WIDOWX
# Value: "oxe_widowx"
OXE_DROID
The Open-X-Embodiment DROID robot with relative joint position actions.
EmbodimentTag.OXE_DROID
# Value: "oxe_droid"
BEHAVIOR_R1_PRO
The Behavior R1 Pro robot.
EmbodimentTag.BEHAVIOR_R1_PRO
# Value: "behavior_r1_pro"
Custom embodiments
NEW_EMBODIMENT
Placeholder tag for any new embodiment during post-training.
EmbodimentTag.NEW_EMBODIMENT
# Value: "new_embodiment"
Usage
from gr00t.data.embodiment_tags import EmbodimentTag
from gr00t.data.types import VLAStepData
# Create VLA step data with embodiment tag
vla_step = VLAStepData(
images={"front_cam": [image_array]},
states={"joint_positions": state_array},
actions={"joint_velocities": action_array},
text="Pick up the apple",
embodiment=EmbodimentTag.UNITREE_G1,
)
# Access embodiment value
print(vla_step.embodiment.value) # "unitree_g1"