发表机构
Florida Institute for Human and Machine Cognition; University of West Florida（佛罗里达人机认知研究所; 西佛罗里达大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究提出机器人本地可运行时编辑的行为系统，结合 Affordance Templates 等架构，在 Unitree H1-2 和 Alex 机器人上快速完成移动操作任务，性能可与近期学习系统媲美。
AI 中文摘要
类人机器人在为人类建造的空间中承担体力要求高、危险且重复性的工作具有巨大价值。然而，适用于这类空间的机器人必须协调移动、全身运动、感知、接触以及操作员监督。我们提出一种机器人本地的、可运行时编辑的行为创作与运行时系统，以应对这些挑战。我们认为，行为架构是实现能力、速度和可靠性的主要推动因素，而运行时可编辑性支持快速的行为创建、适配、扩展与组合。我们的行为架构结合了以对象为中心的 Affordance Templates（ affordance 即可供性，是机器人感知与交互的核心概念）、提供组织与逻辑的树结构，以及通过行为场景和基元场景动作实现的可运行时编辑的感知。操作员界面与机器人保持持续同步，用于运行时创作、监控与修复。动作基元通过支持身体运动与行走并发执行的全身控制器运行。我们的系统在 Unitree H1-2 和 Alex 上完成了六个任务变体的演示：在人类干扰下，34 秒内完成推门穿越，45 秒内按颜色对六个球进行分类；定时创作会话显示，从零创建新的移动操作行为以及适配现有行为仅需数小时。与文献中的方法对比发现，我们的方法可与近期基于学习的系统相媲美。
英文摘要
There is tremendous value in humanoid robots taking on physically demanding, hazardous, and repetitive work in spaces built for humans. However, a useful robot for these spaces must coordinate locomotion, whole-body motion, perception, contact, and operator supervision. We present a robot-local, runtime-editable behavior authoring and runtime system that addresses these challenges. We argue that behavior architecture can be a primary enabler of capability, speed, and reliability, and that runtime editability enables fast behavior creation, adaptation, extension, and combination. Our behavior architecture combines object-centric Affordance Templates, a tree structure that provides organization and logic, and runtime-editable perception through a behavior scene and primitive scene actions. Our operator interface remains continuously synchronized to the robot for runtime authoring, monitoring, and repair. Action primitives execute through a whole-body controller that supports concurrent body motions and walking. Demonstrations of our system cover six task variants on Unitree H1-2 and Alex. We execute a push door traversal in 34 seconds and sort six balls by color in 45 seconds under human disturbance. Timed authoring sessions show scratch creation of new loco-manipulation behaviors and adaptation of existing ones in hours. Comparison against the literature finds our approach to be competitive with recent learned systems.
Comments20 pages, 25 figures, 1 table. Supplementary video: https://www.youtube.com/playlist?list=PLJK5CTyotYqsfgfnXb-09YNFeBose6uEY
