RoboLab-EgoX#
Policy rollouts recorded on NVIDIAβs
RoboLab manipulation benchmark, as
native .mcap episodes.
Each take carries three synchronized camera views with a matching 16-bit depth stream, per-camera intrinsics, joint positions, actions, end-effector pose, and the task instruction. Takes keep the benchmarkβs own success label, so failed rollouts sit alongside successful ones: 632 of the 4,000 takes succeeded, spanning all 28 tasks and 99 background scenes.
In 153 of the 4,000 takes the camera streams carry 80 frames while depth and telemetry carry 81, so align streams by timestamp rather than by index.
Details
Dataset name:
robolabDataset source: https://huggingface.co/datasets/Voxel51/RoboLab-EgoX
Dataset size: 21.85 GB
Dataset license: Apache-2.0
Tags:
multimodal, mcap, robotics, manipulation, depthSupported splits:
N/AZooDataset class:
RoboLabDataset
Example usage
1import fiftyone as fo
2import fiftyone.zoo as foz
3
4dataset = foz.load_zoo_dataset("robolab")
5
6# Rollouts the policy got right
7view = dataset.match({"success": True})
8
9session = fo.launch_app(dataset)
fiftyone zoo datasets load robolab
fiftyone app launch robolab