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AIRoA-0: Long-Horizon, Precise, Cross-Embodiment Manipulation from Handheld Data

1 reports1 reporting sourcesUpdated 2 hours ago

Overview

Event synthesis

This paper introduces AIRoA-0 (A-0), a bimanual manipulation system trained entirely on 16,151 hours of handheld demonstrations recorded using the open-source YUBI gripper, with no robot data collected during training.

Generated from attributed reports · Updated 2 hours ago

Event evidence and corrections

0 attributed source owners. Ownership does not establish independent confirmation. Quantities are reported separately and are never added together.

Reported quantity · training hours: 16151 hours · Basis not reported
Supporting report

“arXiv:2611.03815v1 Announce Type: new Abstract: AIRoA-0 (A-0) is a bimanual manipulation system learned from 16,151 hours of handheld demonstrations, with no robot data collected at any stage. The demonstrations are recorded with YUBI, our open-source handheld gripper, which lets people record manipulation data anywhere with no robot present. From a single instruction, A-0 sorts more than a dozen small parts into the”

Exact source · revision 1

Source owner not reported

Reported quantity · Reported success rate: 78 percent · reported trials
Supporting report

“ir numbered cells and changes the mop pads and brush of a robot vacuum; among other tasks, it unzips a pencil case and folds a towel. It performs these tasks using only a camera on each wrist, with no head or scene camera, at a site where none of its training data was recorded. Across the ten tasks of our evaluation, it averages a success rate of 78%, against 27% for the strongest of four other vision-language-action”

Exact source · revision 1

Source owner not reported

Reported quantity · training time: 4 hours · Basis not reported
Supporting report

“it in under four hours on a single node of eight H200 GPUs.”

Exact source · revision 1

Source owner not reported

Reported quantity · robots: 0 other · Basis not reported
Supporting report

“uch as a bimanual Franka, TX-G2, OpenArm and UR. We are releasing the dataset, to our knowledge the largest open dataset of handheld-gripper demonstrations with task and subtask instructions, together with the pre-trained weights and the post-training recipe. Videos of A-0 on every task are on the project page, https://a-0.airoa.io. Anyone can build the gripper, record a task of their own and post-train the model on”

Exact source · revision 1

Source owner not reported

Reported quantity · trajectories: 0 other · Basis not reported
Supporting report

“arXiv:2611.03815v1 Announce Type: new Abstract: AIRoA-0 (A-0) is a bimanual manipulation system learned from 16,151 hours of handheld demonstrations, with no robot data collected at any stage. The demonstrations are recorded with YUBI, our open-source handheld gripper, which lets people record manipulation data anywhere with no robot present. From a single instruction, A-0 sorts more than a dozen small parts into the”

Exact source · revision 1

Source owner not reported

Reported quantity · datasets: 0 other · Basis not reported
Supporting report

“uch as a bimanual Franka, TX-G2, OpenArm and UR. We are releasing the dataset, to our knowledge the largest open dataset of handheld-gripper demonstrations with task and subtask instructions, together with the pre-trained weights and the post-training recipe. Videos of A-0 on every task are on the project page, https://a-0.airoa.io. Anyone can build the gripper, record a task of their own and post-train the model on”

Exact source · revision 1

Source owner not reported

Reported quantity · models: 0 other · Basis not reported
Supporting report

“uch as a bimanual Franka, TX-G2, OpenArm and UR. We are releasing the dataset, to our knowledge the largest open dataset of handheld-gripper demonstrations with task and subtask instructions, together with the pre-trained weights and the post-training recipe. Videos of A-0 on every task are on the project page, https://a-0.airoa.io. Anyone can build the gripper, record a task of their own and post-train the model on”

Exact source · revision 1

Source owner not reported

Reported quantity · videos: 0 other · Basis not reported
Supporting report

“uch as a bimanual Franka, TX-G2, OpenArm and UR. We are releasing the dataset, to our knowledge the largest open dataset of handheld-gripper demonstrations with task and subtask instructions, together with the pre-trained weights and the post-training recipe. Videos of A-0 on every task are on the project page, https://a-0.airoa.io. Anyone can build the gripper, record a task of their own and post-train the model on”

Exact source · revision 1

Source owner not reported

Artifact availability · weights: reported pending
Supporting report

“uch as a bimanual Franka, TX-G2, OpenArm and UR. We are releasing the dataset, to our knowledge the largest open dataset of handheld-gripper demonstrations with task and subtask instructions, together with the pre-trained weights and the post-training recipe. Videos of A-0 on every task are on the project page, https://a-0.airoa.io. Anyone can build the gripper, record a task of their own and post-train the model on”

Exact source · revision 1

Source owner not reported

Artifact availability · dataset: reported pending
Supporting report

“uch as a bimanual Franka, TX-G2, OpenArm and UR. We are releasing the dataset, to our knowledge the largest open dataset of handheld-gripper demonstrations with task and subtask instructions, together with the pre-trained weights and the post-training recipe. Videos of A-0 on every task are on the project page, https://a-0.airoa.io. Anyone can build the gripper, record a task of their own and post-train the model on”

Exact source · revision 1

Source owner not reported

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11/4
  1. arXiv Robotics — research abstractsSignal
    AIRoA-0: Long-Horizon, Precise, Cross-Embodiment Manipulation from Handheld Data

    This paper introduces AIRoA-0 (A-0), a bimanual manipulation system trained entirely on 16,151 hours of handheld demonstrations recorded using the open-source YUBI gripper, with no robot data collected during training.

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