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is_terminal
bool
2 classes
is_first
bool
2 classes
action.gripper_closedness_action
float32
-1
1
action.terminate_episode
list
action.base_displacement_vector
list
action.rotation_delta
list
action.base_displacement_vertical_rotation
float32
-0.4
0.4
action.world_vector
list
reward
float32
0
1
observation.rotation_delta_to_go
list
observation.orientation_start
list
observation.height_to_bottom
float32
-0.01
1.69
observation.natural_language_instruction
stringclasses
599 values
observation.natural_language_embedding
list
observation.workspace_bounds
list
observation.robot_orientation_positions_box
list
observation.gripper_closedness_commanded
float32
-1
1
observation.base_pose_tool_reached
list
observation.vector_to_go
list
observation.src_rotation
list
observation.gripper_closed
float32
0
1
observation.orientation_box
list
is_last
bool
2 classes
action
list
observation.state
list
timestamp
float32
0
130
frame_index
int64
0
649
episode_index
int64
0
84k
index
int64
0
3.65M
task_index
int64
0
84k
trace.x
float32
0.8
100
trace.y
float32
0
100
false
true
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0.976168
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0.976155
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0.972623
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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[ 0.1730353832244873, -0.6196062564849854, 0.7624784111976624, -0.0690903589129448 ]
0.94787
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0.885735
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0.777646
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0.6613
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0.567024
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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1.4
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0.487433
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
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0
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0.430834
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
[ -5, -5, 0.4000000059604645, 5, 0, 0, 0, 5, 1.7000000476837158 ]
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1.8
9
0
9
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71.300163
82.443207
false
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0
[ 0, 0, 0 ]
[ 0.16062240302562714, -0.6065992116928101, 0.7496838569641113, 0.21026630699634552 ]
0.398002
pick rxbar chocolate from bottom drawer and place on counter
[ 0.042885564267635345, 0.06871598213911057, -0.031140172854065895, -0.013650564476847649, 0.06215057894587517, 0.0801941305398941, 0.012385495007038116, -0.047880418598651886, 0.13628904521465302, -0.06869087368249893, 0.02543465420603752, 0.019282521679997444, 0.07156025618314743, 0.065718...
[ -5, -5, 0.4000000059604645, 5, 0, 0, 0, 5, 1.7000000476837158 ]
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0
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End of preview. Expand in Data Studio

SemanticVLA TraceX 240K · Fractal (RT-1)

🎉 Accepted to CVPR 2026.
✍️ Fei Ni¹, Zhuo Chen², Yifu Yuan³, Zibin Dong³, Xianze Yao³, Shan Luo², Jianye Hao³, Jiankang Deng¹†, Stefanos Zafeiriou¹†
🏫 ¹Imperial College London    ²King's College London    ³Tianjin University
✉️ Primary contact: f.ni@imperial.ac.uk

The Fractal (RT-1) component of TraceX-240K — the trace-annotated trajectory corpus introduced in SemanticVLA. This package is a LeRobot v3.0 repack of Fractal · Google Robot · Open-X-Embodiment fractal20220817 v0.1.0 with dense per-frame end-effector trace labels stored directly in every frame row.

📚 Code · checkpoints · paper: https://github.com/Fei-Ni/SemanticVLA_Offcial

🎬 Sample trace overlays

Each clip shows the orange trace label (per-frame gripper position) overlaid on the original episode camera feed.

episode 17431 episode 34901 episode 43630 episode 61060
episode 17431episode 34901episode 43630episode 61060

🧭 Trace label schema

Dense per-frame end-effector position columns, stored directly in every frame row:

  • trace.xfloat32[1], normalized image-space x coordinate on a [0, 100] scale.
  • trace.yfloat32[1], normalized image-space y coordinate on a [0, 100] scale.

(0, 0) is the top-left corner of the frame, (100, 100) the bottom-right.

📦 Contents

Field Value
HF repo spikefly/SemanticVLA-TraceX-240K-Fractal
Format LeRobot v3.0
Episodes 87,182
Frames 3,786,274
FPS 5
Robot type google_robot
Source dataset Open-X-Embodiment fractal20220817_data v0.1.0
Data file target 100 MB
Video file target 500 MB

Video streams

  • observation.images.image

🧭 Coverage

The upstream Fractal train split has 87,212 episodes. This TraceX v3 package contains the 87,182 episodes with valid dense trace annotations; the 30 episodes without dense trace are excluded (no synthetic fallback inserted).

📂 Sibling datasets in TraceX-240K

DatasetHF RepositoryEmbodiment
Bridgespikefly/SemanticVLA-TraceX-240K-BridgeBridgeData V2 / WidowX
BC-Zspikefly/SemanticVLA-TraceX-240K-BC-ZBC-Z / Google Robot
DROIDspikefly/SemanticVLA-TraceX-240K-DROIDDROID / Franka

✏️ Citation

If you use this dataset, please cite SemanticVLA:

@inproceedings{ni2026semanticvla,
  title     = {SemanticVLA: Towards Semantic Reasoning over Action Memorization via Synergistic Explicit Trace and Latent Action Planning},
  author    = {Ni, Fei and Chen, Zhuo and Yuan, Yifu and Dong, Zibin and Yao, Xianze and Luo, Shan and Hao, Jianye and Deng, Jiankang and Zafeiriou, Stefanos},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2026}
}

📜 License & terms

The trace annotation labels (trace.x / trace.y) are released under the MIT License as part of the SemanticVLA code release. Use of the underlying robot trajectory data is subject to the original source dataset terms (Open-X-Embodiment fractal20220817_data v0.1.0). Please consult the upstream dataset license before use.

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