外观
论文arXiv 2608.215502 个月前
GOLEM：面向电动汽车电池拆解的模块化人形机器人自主系统
GOLEM面向退役EV电池包拆解，采用模块化开源架构，在仿真数字孪生与真实Unitree H1-2上验证。
宇树 H1原文链接：GOLEM: Modular Humanoid Autonomy Towards Electric Vehicle Battery Disassembly（arXiv 2608.21550 · 发布日期：2026-08-21）
GOLEM: Modular Humanoid Autonomy Towards Electric Vehicle Battery Disassembly
GOLEM面向退役EV电池包拆解，采用模块化开源架构，在仿真数字孪生与真实Unitree H1-2上验证。
核心要点
- 退役EV电池包拆解枯燥且危险，目前几乎完全由人工完成。
- 系统将行走、操作、动态稳定、导航和空间记忆解耦为抽象接口模块。
- Docker化ROS 2抽象连接MuJoCo、IsaacLab数字孪生与实体机器人接口。
- 能力阶梯评估报告13.0cm导航精度、抗扰恢复和紧固件抓取成功率变化；源码已开放。
验证范围与局限：验证范围包括MuJoCo和IsaacLab数字孪生及真实Unitree H1-2，任务为EV电池拆解相关导航、稳定与紧固件抓取。
英文摘要 (Abstract)
Disassembling end-of-life electric vehicle (EV) battery packs is dull and dangerous work, performed almost entirely by humans. We present GOLEM (Generalized Open Library of Embodied Modules), an end-to-end, open-source system architecture for EV battery disassembly with the Unitree H1-2 humanoid robot in which walking, manipulation, dynamic stability, navigation, and spatial memory are independent modules with abstract interfaces, so that methods are easily developed, interchanged, and compared. GOLEM is deployed as a Docker-based ROS 2 abstraction in which MuJoCo and IsaacLab digital twins expose interfaces matching the physical robot. GOLEM's composability and per-module customization enable development and demonstration of humanoid EV battery disassembly, from simulation to reality. GOLEM provides fair comparison between humanoid modules, enabling evaluation as a capability ladder, in which one module is characterized at a time and added as a rung: LiDAR-inertial navigation places the robot within 13.0cm of a 6m goal; a learned standing controller recovers from external disturbances that sampling-based lower-body MPC does not; and grasping loosened fasteners from a real Hyundai Ioniq 5 pack degrades from 97% tethered to 87% free-standing to 37% under navigation-induced pose variance. Source code is available at the project page https://golem-humanoid.github.io
作者：Max Conway, William Xie, Allen Devaraj, Yutong Zhang, Niraj Pudasaini, Mateo Feit, Adam Abid, Zachary Allen, Chen Liu, Xuan Tan
来源
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