HOMIE：基于同构外骨骼驾驶舱的人形机器人移动操作
HOMIE: Humanoid Loco-Manipulation with Isomorphic Exoskeleton Cockpit
AI总结：
本文提出半自主遥操作系统HOMIE，结合强化学习身体控制策略、同构外骨骼手臂和动觉手套，实现高效、精确且经济的人形机器人全身移动操作。
摘要：
具备泛化能力的人形机器人移动操作面临重大挑战，需要协调的全身控制以及精确且富接触的物体操作。为此，本文提出了HOMIE，这是一个半自主遥操作系统，它结合了映射到踏板的用于身体控制的强化学习策略、用于手臂控制的同构外骨骼手臂，以及用于手部控制的动觉手套，形成了一个统一的驾驶舱，可自由操作人形机器人并建立数据飞轮。该策略引入了新颖的设计，包括上半身姿态课程、高度跟踪奖励以及对称性利用。这些特性使系统能够执行行走和下蹲至特定高度，同时无缝适应任意上半身姿态。外骨骼通过消除对逆动力学的依赖，提供了更快、更精确的手臂控制。手套采用霍尔传感器代替伺服电机，使得即使是紧凑型设备也能实现15个或更多自由度，并自由适应任何灵巧手型号。与以往的遥操作系统相比，HOMIE以其卓越的效率脱颖而出，能在一半的时间内完成任务；其扩展的工作范围允许用户自由触及高低区域并与任何物体交互；且其极具经济性，价格仅为500美元。该系统完全开源，演示和代码可在我们的 https://homietele.github.io/ 找到。
英文摘要：
Generalizable humanoid loco-manipulation poses significant challenges, requiring coordinated whole-body control and precise, contact-rich object manipulation. To address this, this paper introduces HOMIE, a semi-autonomous teleoperation system that combines a reinforcement learning policy for body control mapped to a pedal, an isomorphic exoskeleton arm for arm control, and motion-sensing gloves for hand control, forming a unified cockpit to freely operate humanoids and establish a data flywheel. The policy incorporates novel designs, including an upper-body pose curriculum, a height-tracking reward, and symmetry utilization. These features enable the system to perform walking and squatting to specific heights while seamlessly adapting to arbitrary upper-body poses. The exoskeleton, by eliminating the reliance on inverse dynamics, delivers faster and more precise arm control. The gloves utilize Hall sensors instead of servos, allowing even compact devices to achieve 15 or more degrees of freedom and freely adapt to any model of dexterous hands. Compared to previous teleoperation systems, HOMIE stands out for its exceptional efficiency, completing tasks in half the time; its expanded working range, allowing users to freely reach high and low areas as well as interact with any objects; and its affordability, with a price of just $500. The system is fully open-source, demos and code can be found in our https://homietele.github.io/.
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。
