Collaborative Research Resources: An Experimental Platform for Humanoid Robotics Research

协作研究资源：仿人机器人研究实验平台

• 批准号: 0224419
• 负责人: Jessica Hodgins
• 金额: $ 100万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-03-15 至 2008-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0224419&HistoricalAwards=false
• 关键词: Collaborative; Research; Resources; Experimental; Platform

This award provides funds to build a state of the art humanoid robot experimental facility at CMU's Robotics Institute. Developing humanoid robots pushes robotics and automation technology forward. Researchers build humanoid robots to test and explore their theories about how humans work. Humanoid robots are beginning to play an economically important role in the service segment of our society. Primarily, humanoid robots inspire. For example Japan is publicizing its humanoid robotics research to get more children interested in science and engineering, currently a major concern in the U.S.The PIs will purchase an upper body humanoid from Sarcos Research Corporation as well as two smaller robots and an advanced interface device. Using the proposed equipment, the PIs will undertake a number of projects which fall into four broad classes: core robotics and vision research that substantially increases the capabilities and skills of robots (Atkeson, Hebert, Rizzi, Pollard), authoring tools that will make it easier for people who are not roboticists and perhaps even not programmers to develop new applications on robots (Hodgins, Hudson, Kuffner), application prototyping and assessment of humanoid robots in various application domains (Pausch, Kiesler), and unifying applications, which involve a large number of interdisciplinary researchers. In addition to the expected robotics researchers, the team includes researchers from HCI and sociology to work on how these robots might be made easy to use and how they will fit into society. Taken together, these projects will significantly expand the ability both to control humanoid robots and to develop applications on them. These projects will also increase fundamental understanding of the power of the human form in a robot, and our fundamental understanding of human motion. The PIs will encourage other researchers at CMU and in the U.S. to use the facility, taking advantage of strengths in vision, speech, and reasoning. Finally, the PIs are using humanoid robots to explore computational models of how human behavior is generated. Using a humanoid robot as a research tool forces the researchers to deal with a complex physical apparatus and complex tasks. The knowledge required to recreate human motions will also serve to increase our understanding of how people move and may lead to advances in physical rehabilitation and sports medicine. In contrast to most biomechanical research, the PIs will attempt to refine scientific understanding of both the functional components of human motion such as locomotion and grasping and also the subtle stylistic components that make it appear normal, humanlike, and expressive. Combining these two components should make the models useful for analyzing the performance of aspiring athletes as well as diagnosing individual problems with locomotion and manipulation.

该奖项为CMU机器人研究所建造最先进的人形机器人实验设施提供资金。开发人形机器人推动了机器人技术和自动化技术的发展。研究人员建造人形机器人来测试和探索他们关于人类如何工作的理论。人形机器人开始在我们社会的服务领域发挥重要的经济作用。Priestion，humanoid robots inspire.例如，日本正在宣传其人形机器人研究，以吸引更多的孩子对科学和工程感兴趣，目前这是美国的一个主要关注点。使用拟议的设备，PI将进行一些项目，这些项目分为四大类：核心机器人和视觉研究，大大提高了机器人的能力和技能（Atkeson，Hebert，Rizzi，Pollard），这些创作工具将使那些不是机器人专家甚至可能不是程序员的人更容易在机器人上开发新的应用程序（Hodgins，哈德逊，Kuffner），在各种应用领域中的人形机器人的应用原型和评估（Pausch，Kiesler），以及统一应用，这些涉及大量跨学科的研究人员。除了预期的机器人研究人员外，该团队还包括来自HCI和社会学的研究人员，致力于研究如何使这些机器人易于使用以及如何适应社会。总的来说，这些项目将大大扩展控制人形机器人和开发应用程序的能力。这些项目还将增加对机器人中人类形体力量的基本理解，以及我们对人类运动的基本理解。PI将鼓励CMU和美国的其他研究人员使用该设施，利用视觉，语言和推理方面的优势。最后，PI正在使用人形机器人来探索人类行为如何产生的计算模型。使用人形机器人作为研究工具迫使研究人员处理复杂的物理装置和复杂的任务。重建人体运动所需的知识也将有助于增加我们对人们如何运动的理解，并可能导致身体康复和运动医学的进步。与大多数生物力学研究相反，PI将试图完善对人类运动的功能组件（如运动和抓握）以及使其看起来正常，人性化和表现力的微妙风格组件的科学理解。结合这两个组成部分应该使模型用于分析有抱负的运动员的表现，以及诊断与运动和操作的个人问题。