NRI/Collaborative Research: Models and Instruments for Integrating Effective Human-Robot Teams into Manufacturing
NRI/协作研究:将有效的人机团队集成到制造中的模型和工具
基本信息
- 批准号:1426824
- 负责人:
- 金额:$ 59万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-09-01 至 2019-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Robots for application in collaborative manufacturing must perform manual work side-by-side with people. Such robots offer the flexibility to work on many different tasks and promise to transform manufacturing by improving the quality and efficiency of manual processes in small shops and in facilitates that manufacture highly customized products. However, in order to meet this promise, robots must be effectively integrated into existing manufacturing teams and practices. To enable this integration, this National Robotics Initiative (NRI) award supports fundamental research on the methods and instruments that manufacturing engineers will need to form effective human-robot teams based on task requirements and worker skills. These methods will also enable robots to adapt to changes in workflow to maximize safety and efficiency. The effective integration of collaborative robots into manufacturing promises improvements in many industries that have not yet benefited from robotic technology. Therefore, results from this research will contribute to the competitiveness of U.S. manufacturing and benefit the U.S. economy and society. The research will involve contributions from multiple disciplines, including robotics, human factors, computer science, and manufacturing, and by academic and industry collaborators. These collaborations will help the dissemination of research results into manufacturing organizations and the integration of research into undergraduate and graduate curriculum in engineering.Advancements in robotics promise the use of collaborative robots that perform interdependent work with people in order to improve quality, efficiency, and safety in industrial manufacturing. However, integrating collaborative robots into these processes and ensuring their efficient operation pose significant research challenges, including the optimal allocation of work based on task requirements and constraints, the formation of human-robot teams, and the dynamic adaptation of teamwork to workflow changes. This research will address these research challenges, enabling the seamless integration of collaborative robots into these processes and achieving efficient and safe collaboration between human and robot workers. The research team will create novel methods for optimal allocation of tasks to human and robot workers based on task constraints and worker skills, design new tools that utilize these methods to facilitate workflow design for human-robot teams, and develop novel mechanisms that enable robots to more efficiently and safely collaborate with human workers in the planned manufacturing operations. These methods and instruments will be validated in real-world manufacturing operations and disseminated through industry workshops, engineering curricula, and a public outreach program.
协同制造中应用的机器人必须与人肩并肩地进行体力劳动。这种机器人可以灵活地完成许多不同的任务,并有望通过提高小商店手工流程的质量和效率来改变制造业,并促进高度定制产品的生产。然而,为了实现这一承诺,机器人必须有效地集成到现有的制造团队和实践中。为了实现这种整合,国家机器人计划(NRI)奖支持制造工程师根据任务要求和工人技能组建有效的人机团队所需的方法和仪器的基础研究。这些方法还将使机器人能够适应工作流程的变化,以最大限度地提高安全性和效率。协作机器人与制造业的有效整合有望改善许多尚未受益于机器人技术的行业。因此,本研究的结果将有助于提高美国制造业的竞争力,有利于美国经济和社会。这项研究将涉及多个学科的贡献,包括机器人、人为因素、计算机科学和制造业,以及学术界和工业界的合作者。这些合作将有助于将研究成果传播到制造组织,并将研究成果整合到工程专业的本科和研究生课程中。机器人技术的进步保证了协作机器人的使用,协作机器人可以与人进行相互依赖的工作,从而提高工业制造的质量、效率和安全性。然而,将协作机器人集成到这些过程中并确保其高效运行,提出了重大的研究挑战,包括基于任务需求和约束的工作优化分配,人-机器人团队的形成以及团队对工作流程变化的动态适应。本研究将解决这些研究挑战,使协作机器人无缝集成到这些过程中,实现人类和机器人工人之间高效、安全的协作。研究小组将根据任务限制和工人技能,为人类和机器人工人的任务优化分配创造新的方法,设计利用这些方法促进人机团队工作流设计的新工具,并开发新的机制,使机器人能够在计划的制造操作中更有效、更安全地与人类工人合作。这些方法和工具将在现实世界的制造操作中得到验证,并通过工业研讨会、工程课程和公共推广计划进行传播。
项目成果
期刊论文数量(5)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Effective task training strategies for human and robot instructors
人类和机器人教练的有效任务训练策略
- DOI:10.1007/s10514-015-9461-0
- 发表时间:2015
- 期刊:
- 影响因子:3.5
- 作者:Sauppé, Allison;Mutlu, Bilge
- 通讯作者:Mutlu, Bilge
Designing Interface Aids to Assist Collaborative Robot Operators in Attention Management
设计界面辅助工具以协助协作机器人操作员进行注意力管理
- DOI:
- 发表时间:2021
- 期刊:
- 影响因子:0
- 作者:Henrichs, Curt;Zhao, Fangyun;Mutlu, Bilge
- 通讯作者:Mutlu, Bilge
Authr: A Task Authoring Environment for Human-Robot Teams
Authr:人机团队的任务创作环境
- DOI:10.1145/3379337.3415872
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Schoen, Andrew;Henrichs, Curt;Strohkirch, Mathias;Mutlu, Bilge
- 通讯作者:Mutlu, Bilge
Optimizing Makespan and Ergonomics in Integrating Collaborative Robots Into Manufacturing Processes
将协作机器人集成到制造流程中优化完工时间和人体工程学
- DOI:10.1109/tase.2018.2789820
- 发表时间:2018
- 期刊:
- 影响因子:5.6
- 作者:Pearce, Margaret;Mutlu, Bilge;Shah, Julie;Radwin, Robert
- 通讯作者:Radwin, Robert
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Bilge Mutlu其他文献
Robust, low-cost, non-intrusive sensing and recognition of seated postures
稳健、低成本、非侵入式的坐姿传感和识别
- DOI:
10.1145/1294211.1294237 - 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Bilge Mutlu;Andreas Krause;J. Forlizzi;Carlos Guestrin;J. Hodgins - 通讯作者:
J. Hodgins
The Social Impact of a Robot Co-Worker in Industrial Settings
工业环境中机器人同事的社会影响
- DOI:
10.1145/2702123.2702181 - 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Allison Sauppé;Bilge Mutlu - 通讯作者:
Bilge Mutlu
Characterizing Barriers and Technology Needs in the Kitchen for Blind and Low Vision People
描述盲人和低视力人士厨房中的障碍和技术需求
- DOI:
10.48550/arxiv.2310.05396 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Ru Wang;Nihan Zhou;Tam Nguyen;Sanbrita Mondal;Bilge Mutlu;Yuhang Zhao - 通讯作者:
Yuhang Zhao
Manually Acquiring Targets From Multiple Viewpoints Using Video Feedback
使用视频反馈从多个视角手动获取目标
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Bailey Ramesh;Anna Konstant;Pragathi Pravenna;Emmanuel Senft;Michael Gleicher;Bilge Mutlu;M. Zinn;R. Radwin - 通讯作者:
R. Radwin
Proceedings of the Third international conference on Social Robotics
第三届社会机器人国际会议论文集
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:0
- 作者:
Bilge Mutlu;C. Bartneck;Jaap Ham;V. Evers - 通讯作者:
V. Evers
Bilge Mutlu的其他文献
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{{ truncateString('Bilge Mutlu', 18)}}的其他基金
Collaborative Research: HCC: Medium: Designing Social Companion Robots for Long-term Interaction
合作研究:HCC:媒介:设计用于长期交互的社交伴侣机器人
- 批准号:
2312354 - 财政年份:2023
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
Integrating Robots into the Future of Work
将机器人融入未来的工作
- 批准号:
2152163 - 财政年份:2022
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
Collaborative Research: HCC: Small: PATHWiSE - Supporting Teacher Authoring of Robot-Assisted Homework
合作研究:HCC:小型:PATHWiSE - 支持教师编写机器人辅助作业
- 批准号:
2202803 - 财政年份:2022
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
Designing and Testing Companion Robots to Support Informal, In-home STEM Learning
设计和测试伴侣机器人以支持非正式的家庭 STEM 学习
- 批准号:
1906854 - 财政年份:2019
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
NRI: INT: COLLAB: Program Verification and Synthesis for Collaborative Robots
NRI:INT:COLLAB:协作机器人的程序验证和综合
- 批准号:
1925043 - 财政年份:2019
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
ROBO-VI: A Virtual-Internship-Based Hybrid Learning Technology to Prepare Traditional and Non-Traditional Students to Work with Collaborative Robots
ROBO-VI:一种基于虚拟实习的混合学习技术,帮助传统和非传统学生做好使用协作机器人的准备
- 批准号:
1822872 - 财政年份:2018
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
EAGER: Representations and Methods for Verifiable Human-Robot Interactions
EAGER:可验证的人机交互的表示和方法
- 批准号:
1651129 - 财政年份:2016
- 资助金额:
$ 59万 - 项目类别:
Standard Grant
CAREER: Designing Socially Adept Robots
职业:设计社交机器人
- 批准号:
1149970 - 财政年份:2012
- 资助金额:
$ 59万 - 项目类别:
Continuing Grant
HCC: Small: Embodied Mediated Communication in Collaborative Work
HCC:小型:协作工作中的体现中介沟通
- 批准号:
1117652 - 财政年份:2011
- 资助金额:
$ 59万 - 项目类别:
Continuing Grant
HCC: Small: Designing Effective Gaze Mechanisms for Cross-Modal Embodied Agents
HCC:小:为跨模式实体代理设计有效的注视机制
- 批准号:
1017952 - 财政年份:2010
- 资助金额:
$ 59万 - 项目类别:
Continuing Grant
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