Latching an RJ45 Cable into a High-Density Switch Port - FastUMI Handheld Gripper
Overview
Latching an RJ45 Cable into a High-Density Switch Port - FastUMI Handheld Gripper is a video dataset. It covers English. Typical applications include robotics & embodied AI. Relevant sectors: Technology & IT, AI & Machine Learning and Manufacturing & Industrial. The provider lists it without a licence fee; terms should still be confirmed before commercial use.
Primary applications
What the listing offers
- A sample is indicated as available from the provider.
- Version 1.0 as published by the source.
A handheld-gripper demonstration of a high-precision network-cabling task: inserting and latching an RJ45 connector into a densely populated switch port on a server rack. Recorded on a FastUMI-style handheld gripper rig with SLAM-tracked pose — five synchronised streams at 25.45 fps: a head RGB view (1280×720), a true 16-bit depth stream (1280×720, FFV1, lossless), a colourised depth visualisation (1280×720), and two wrist RGB views (1920×1080). Packaged as a HuggingFace LeRobot v2.1 dataset: 1 episode, 753 frames (30 s), QC-complete with 0 Tier-1 FAILs. The parquet carries a 7-DOF state and 7-DOF action vector, gripper width in metres and normalised form, and per-frame validity flags for the gripper marker and the SLAM track — so consumers can filter to frames with a trustworthy pose. Useful for high-precision insertion and connector-mating tasks, depth-aware manipulation, and SLAM-conditioned policy learning.
Technical specifications
- Modalities
- Video
Related datasets
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Egocentric, multi-view human demonstrations of data-center / IT-infrastructure manipulation activities, captured with a FastUMI handheld egocentric rig (Universal…
- Language
- English
- Volume
- —
- Domain
- Technology & IT +2
- Use case
- LLM pre-training
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