CAREER: Understanding and Enabling Human-Robot Collaboration with Groups of People

职业：理解并实现人机与人群的协作

基本信息

批准号：
1942085
负责人：
Malte Jung
金额：
$ 55万
依托单位：
Cornell University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-03-01 至 2025-02-28
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1942085&HistoricalAwards=false
关键词：
CAREER Understanding Enabling Human Robot

项目摘要

How well a team performs depends on its internal dynamics. As robots become more and more integrated into teamwork in areas that span surgery, space exploration missions, search and rescue, or manufacturing, it is important to understand how robots impact team dynamics and a team's ability to perform. The goal of this project is to investigate the impact that a robot has on a team's dynamics and then to use this understanding to develop novel ways for robots to directly shape those dynamics to improve a team's likelihood to succeed. Findings from this work will advance our understanding of robot assisted teamwork. Further the project will develop educational activities that allow children and students to develop the skills necessary to succeed in a work environment that includes robots. While most work is performed by groups and teams, research on human-robot collaboration has focused predominantly on dyadic interactions, i.e. a single human collaborating with a single robot. The effectiveness of teams depends on the quality of its interpersonal interactions. Transforming human-robot collaboration from a dyadic towards a group focus raises novel questions about such teaming. In particular: 1) how a robot's behavior influences both human-robot interactions and human-human interpersonal interactions in a group of people, 2) how robots can deliberately shape human-human interpersonal interactions, and 3) what the consequences of such influence are for a team's overall effectiveness. This project investigates how a robot's resource allocation behavior impacts people's interactions with each other and their ability to perform as a team. Allocation behavior refers to behavior associated with a robot's allocation of resources and tasks between several people (e.g. handing over a tool or building block to a team member, allocating social attention and gaze, or providing assistance). This project will: 1) use lab and field studies to develop basic understanding about allocation behavior exhibited by people and robots and how such behavior affects a group's interaction, 2) use an iterative design approach combined with an online and laboratory based task to develop and evaluate allocation behaviors for robots to shape a group's interaction in desirable ways, and 3) examine how a robot's resource allocation behavior during collaborative tasks affects all dimensions of team effectiveness.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

团队的表现效果取决于其内部动力。随着机器人越来越多地整合到跨越手术，太空探索任务，搜索和救援或制造业领域的团队合作中，重要的是要了解机器人如何影响团队动态和团队的表现能力。该项目的目的是调查机器人对团队动态的影响，然后利用这种理解来为机器人直接塑造这些动态以提高团队成功的可能性。这项工作的发现将提高我们对机器人协助团队合作的理解。此外，该项目将开发教育活动，使儿童和学生能够在包括机器人在内的工作环境中发展成功的技能。尽管大多数工作是由小组和团队进行的，但对人类机器人协作的研究主要集中在二元互动上，即与单个机器人合作的单一人类合作。团队的有效性取决于其人际关系互动的质量。将人类机器人的合作从二元运动转变为小组的焦点，提出了有关这种团队的新颖问题。特别是：1）机器人的行为如何影响一组人的人类机器人相互作用和人类人类际交往，2）机器人如何故意刻薄地塑造人类人类际交往，3）3）这种影响的后果对团队的整体有效性有何影响。该项目调查了机器人的资源分配行为如何影响人们彼此之间的互动及其团队表现的能力。分配行为是指与机器人在几个人之间的资源和任务分配相关的行为（例如，将工具或构建块移交给团队成员，分配社会关注和凝视或提供帮助）。该项目将：1）使用实验室和现场研究对人和机器人表现出的分配行为发展基本了解，以及这种行为如何影响团队的互动，2）使用迭代设计方法与基于在线和实验室的任务相结合，以发展和评估机器人以良好的方式塑造一群人的效率，以及在机器人的资源分配方面的合作效果，并评估机器人的互动，以及3） NSF的法定使命，并使用基金会的知识分子优点和更广泛的影响审查标准来评估值得支持。