发表机构
Texas Robotics; Walker Department of Mechanical Engineering, The University of Texas at Austin; The University of Texas at Austin（德克萨斯机器人研究所; 德克萨斯大学奥斯汀分校沃克机械工程学院; 德克萨斯大学奥斯汀分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出一种机器人运行时重组框架，支持现场快速集成未知软件、硬件与计算负载，将重配置时间缩至数分钟，在灾难响应场景中验证了其灵活性与实用性。
AI 中文摘要
大多数机器人的子系统紧密耦合，尽管是其复杂性的自然结果，但会形成整体式设计，在初始部署后难以适应且耗时。为解决这一挑战，我们提出了一种框架及配套抽象，用于运行时重组，使机器人能快速集成此前未知的模块化软件、硬件与计算负载。我们的方法允许非专家用户通过真正的即插即用流程，在现场快速添加新能力。关键在于，新资源不仅对主机机器人立即可用，还会共享给分布式对等节点，使计算受限的系统能访问强大的远程新能力。我们的框架将重新配置时间缩短至数分钟，无需开发者介入，而传统手动集成通常需要数小时的专家工作。我们在两个灾难响应场景中演示了该方法，包括在运行中的核反应堆设施进行放射源定位，以及在黑暗、难以到达的空间开展热引导人员搜索。这些演示表明，现场重组能为动态需求提供及时、灵活且可及的适应，代表着向创建能随所支持的任务、技术和环境快速演进的机器人迈出的关键一步。
英文摘要
The tight coupling of subsystems in most robots, though a natural consequence of their complexity, leads to monolithic designs that are time-consuming and difficult to adapt after initial deployment. To address this challenge, we present a framework and supporting abstractions for recomposition during runtime that enable robots to quickly integrate previously unseen modular software, hardware, and compute payloads. Our approach allows non-expert users to quickly add new capabilities in the field through a true plug-and-play process. Crucially, new resources are not only immediately available to a host robot but are also shared with distributed peers, enabling compute-constrained systems to access powerful new remote capabilities. Our framework reduces reconfiguration time to a matter of minutes with no developer intervention, in stark contrast to the hours of expert effort often required for traditional manual integration. We demonstrate our method in two disaster response scenarios, including radioactive source localization at an operational nuclear reactor facility and a thermal-guided search for people in dark, difficult-to-reach spaces. These demonstrations show how in-field recomposition provides timely, flexible, and accessible adaptation to dynamic requirements, representing a critical step toward creating robots that can quickly evolve alongside the tasks, technologies, and environments they support.
