EmbodimentSemantic

A Spatial Scene-Graph Dataset and Benchmark for Vision-Language Models on Embodied Manipulation Trajectories

Hassan Jaber¹ · Refinath S N² · Luca Cagliero¹ · Christopher E. Mower² · Haitham Bou-Ammar²³

¹Politecnico di Torino · ²Huawei Noah's Ark Lab · ³University College London

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Overview

EmbodimentSemantic is a benchmark dataset for evaluating whether vision-language models (VLMs) can recover exact spatial scene graphs from robot manipulation observations — and whether injecting those scene graphs into existing VLA policies improves downstream control.

The dataset has two components:

• LIBERO Simulator Benchmark — 500 demonstrations across 10 LIBERO-Spatial tasks (62,250 paired timesteps, 124,500 RGB frames). Ground-truth scene graphs are derived automatically from MuJoCo geometry, giving exact triplet-level supervision without manual annotation.
• SO101 Real-Robot Dataset — 257 teleoperated episodes across 5 tabletop bowl-placement tasks, collected with the low-cost SO101 arm. Includes external-camera, wrist-camera, and depth streams in LeRobot format.

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Files

File	Size	Description
libero_spatial_v5.zip	2.91 GB	LIBERO simulator benchmark: HDF5 demos with scene-graph annotations embedded under obs/agentview_scene_graph and obs/robot0_eye_in_hand_scene_graph
SO1001_dataset.zip	6.13 GB	SO101 real-robot dataset in LeRobot format

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Dataset Statistics

LIBERO Simulator Benchmark

Attribute	Value
Tasks	10
Demonstrations	500 (50 per task)
Recorded frames per camera	62,250
Total recorded frames (both cameras)	124,500
Frames per demo	75–197 (mean 124.5)
Cameras	agentview, eye_in_hand
RGB resolution	128 × 128
Mean triplets / frame (agentview)	42.0
Mean triplets / frame (eye_in_hand)	16.73

SO101 Real-Robot Dataset

Attribute	Value
Tasks	5
Demonstrations	257 (47–53 per task)
Total recorded frames (both cameras)	240,598
VLM eval frames (both cameras)	8,252
Cameras	agent_view, wrist
Frame rate	30 FPS (1 frame/sec sampled)
Format	LeRobot

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Spatial Ontology

Objects (LIBERO): akita_black_bowl_1, akita_black_bowl_2, cookies_1, glazed_rim_porcelain_ramekin_1, plate_1, wooden_cabinet_1, flat_stove_1

Objects (SO101): black_bowl, red_drawer, black_stove, cookie, white_plate

Relations (both):

Relation	Description
is_left_of / is_right_of	Lateral world-frame ordering
is_in_front_of / is_behind	Depth world-frame ordering
is_on_top_of / is_below_of	Vertical support / stacking
is_inside / contains	Containment

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