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

• 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

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.

一个团队的表现如何取决于它的内部动力。随着机器人越来越多地融入手术、太空探索任务、搜救或制造等领域的团队合作，了解机器人如何影响团队活力和团队的执行能力是很重要的。这个项目的目标是调查机器人对团队动态的影响，然后利用这种理解开发新的方法，让机器人直接塑造这些动态，以提高团队成功的可能性。这项工作的发现将促进我们对机器人辅助团队合作的理解。此外，该项目将开展教育活动，使儿童和学生能够发展在包括机器人的工作环境中取得成功所需的技能。虽然大多数工作是由团体和团队完成的，但关于人-机器人协作的研究主要集中在二元交互上，即一个人与一个机器人协作。团队的有效性取决于其人际互动的质量。将人类与机器人的协作从二元协作转变为专注于群体的协作，引发了关于这种协作的新问题。具体地说：1)机器人的行为如何影响一群人中的人与机器人互动和人与人之间的互动；2)机器人如何刻意塑造人与人之间的人际互动；以及3)这种影响对团队整体有效性的影响是什么。这个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以及他们作为一个团队的能力。分配行为是指与机器人在几个人之间分配资源和任务相关的行为(例如，将工具或积木交给团队成员，分配社会注意力和凝视，或提供帮助)。该项目将：1)利用实验室和实地研究来发展对人类和机器人所表现出的分配行为以及这种行为如何影响群体互动的基本理解；2)使用迭代设计方法，结合在线和基于实验室的任务来开发和评估机器人的分配行为，从而以理想的方式塑造群体互动；以及3)研究机器人在协作任务期间的资源分配行为如何影响团队效率的各个方面。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Designing Robot Sound-In-Interaction: The Case of Autonomous Public Transport Shuttle Buses

设计机器人声音交互：自动公共交通穿梭巴士案例

• DOI: 10.1145/3568162.3576979
• 发表时间: 2023
• 期刊: Human Robot Interaction
• 作者: Pelikan, Hannah R.;Jung, Malte F.
• 通讯作者: Jung, Malte F.