SuperSuit：一种用于可扩展移动操作的同构双模接口
SuperSuit: An Isomorphic Bimodal Interface for Scalable Mobile Manipulation
AI总结：
SuperSuit 提出了一种双模数据采集框架，通过同构运动学接口实现移动机械臂的高效长周期演示和策略训练。
摘要：
高质量、长周期的演示对于具身AI至关重要，但为紧密耦合的轮式移动机械臂获取此类数据仍然是一个基本瓶颈。与固定基座系统不同，移动机械臂需要在SE(2)运动和精确操作之间持续协调，暴露了现有远程操作和可穿戴接口的局限性。我们提出了SuperSuit，一种双模数据采集框架，支持在共享运动学接口下的机器人回路远程操作和主动演示。两种模式都产生结构上相同的关节空间轨迹，使数据混合无需修改下游策略。在运动方面，SuperSuit将自然人类的步态映射到连续的平面基底速度，消除了离散命令切换。在操作方面，它在两种模式中都采用严格同构的可穿戴臂，而策略训练在移位不变的delta-关节表示中进行，以缓解校准偏移和结构刚度，而无需逆运动学。在实际移动操作任务上的实验表明，主动模式相比远程操作基线的演示吞吐量提高了2.6倍，当在固定数据集大小下用主动演示替代远程操作数据时，策略性能相当，且随着主动数据量的增加，性能呈单调改善。这些结果表明，跨采集模式的一致运动学表示能够实现长周期移动操作的可扩展数据采集。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
