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CAREER: Human-Aware Autonomy for Team-Oriented Environments

CAREER: Human-Aware Autonomy for Team-Oriented Environments
职业:面向团队的环境的人类意识自治
批准号:
1350160
负责人:
Julie Shah
金额:
$39.86万
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
项目状态:
已结题
起止时间:
2014-08-01 至 2020-09-30

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中文摘要
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英文摘要
Robots are an increasingly common presence in human environments, working alongside people in factories, hospitals, and military field operations. However, today people must change how they work to accommodate robots in their workspace. This poses a significant barrier to adoption of robot technology by creating inefficiencies. This project provides an integrated research and educational approach to develop intelligent robotic technologies that more seamlessly integrate with human work environments. The technical approach translates qualitative and quantitative insights from human studies into explicit computational models, and exploits these models to redesign robot algorithms for learning, decision-making, and control. The research effort specifically investigates three types modifications to robot behavior: (1) modifying robot motion planning using anticipatory signals of human motion, (2) customizing robot task plans using statistical models of human task execution, and (3) inferring and applying human domain expertise to expedite automated planning for mixed human-robot teams. Human subject experimentation is planned to assess ease-of-interaction, worker trust, and task performance, and the approach is validated using metrics to quantitatively assess the degree to which a robot's behavior preserves natural human workflow. By designing robot autonomy that minimizes disruption to human workflow, the approach supports graceful transitions from robotic work back to human work and vice versa.
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Collaborative Research: SCH: An AI Coach for Enhancing Teamwork in the Cardiac Operating Room
Doctoral Mentoring Consortium at the International Conference on Autonomous Agents and Multiagent Systems
NRI: INT: COLLAB: Collaborative Task Planning and Learning through Language Communication in a Human-Robot Team.
RSS 2015 Workshop on Women in Robotics
国内基金
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