aiqbench analysis
This paper presents a wearable teleoperation device that collects whole-body demonstrations for imitation-learning policies, both with the robot present and without it. Its main contribution is a data pipeline: arms mechanically matched to the robot's remove inverse kinematics and retargeting from the conversion step. The reported result, that 100 robot-free episodes on top of a 10-episode robot-grounded seed match policy quality on three real-robot tasks, is a practical signal that operator time, not robot uptime, may become the limiting factor for robot learning datasets. Results are limited to three tasks on one platform, so generalization is still open.
SuperSuit: An Isomorphic Bimodal Interface for Scalable Mobile Manipulation
arXiv:2603.06280v2 Announce Type: replace Abstract: Long-horizon mobile manipulation needs whole-body demonstrations, and collecting them is the bottleneck. Keeping the robot in the loop ties the dataset to robot uptime, while recording human motion without it instead requires a conversion step that decides the joint-space action the policy learns. SuperSuit is a single wearable that both teleoperates a wheeled bimanual robot and, with the robot absent, records demonstrations for it. Its arms are mechanically aligned to the robot's, so recorded joint motion needs no inverse kinematics and no retargeting; one body-worn tracker drives the torso and the planar base through a deadband that keeps posture micro-sway out of the base command. Both roles emit the same 22-D command over the torso, planar base, two 7-DoF arms, and two grippers, with arm targets expressed as forward-looking increments of the observed joint state. On three real-robot tasks this lets active demonstrations replace most robot-in-the-loop collection without changing policy quality. With a 10-episode robot-grounded seed held fixed, the remaining 100 episodes can be recorded without the robot, whereas active-only training falls well short. SuperSuit moves the limit on dataset size from the robot to the operator.
Abstract:Long-horizon mobile manipulation needs whole-body demonstrations, and collecting them is the bottleneck. Keeping the robot in the loop ties the dataset to robot uptime, while recording human motion without it instead requires a conversion step that decides the joint-space action the policy learns. SuperSuit is a single wearable that both teleoperates a wheeled bimanual robot and, with the robot absent, records demonstrations for it. Its arms are mechanically aligned to the robot's, so recorded joint motion needs no inverse kinematics and no retargeting; one body-worn tracker drives the torso and the planar base through a deadband that keeps posture micro-sway out of the base command. Both roles emit the same 22-D command over the torso, planar base, two 7-DoF arms, and two grippers, with arm targets expressed as forward-looking increments of the observed joint state. On three real-robot tasks this lets active demonstrations replace most robot-in-the-loop collection without changing policy quality. With a 10-episode robot-grounded seed held fixed, the remaining 100 episodes can be recorded without the robot, whereas active-only training falls well short. SuperSuit moves the limit on dataset size from the robot to the operator.
Robotics (cs.RO)
arXiv:2603.06280 [cs.RO]
(or arXiv:2603.06280v2 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2603.06280 Focus to learn more arXiv-issued DOI via DataCite
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Full text under the publisher's open licence · 278 words
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