CRII: CPS: A Bi-Trust Framework for Collaboration-Quality Improvement in Human-Robot Collaborative Contexts

CRII：CPS：人机协作环境中协作质量改进的双信任框架

• 批准号: 2104742
• 负责人: Weitian Wang
• 金额: $ 17.35万
• 依托单位: Montclair State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2104742&HistoricalAwards=false
• 关键词: CRII; CPS; Bi; Trust; Framework

Collaborative robots have been widely employed to assist humans in an increasing number of areas. Just as human-human collaboration, the trust in human-robot teams has a property of bidirectional. However, few studies have been conducted on both human-trusting-robot issue and robot-trusting-human issue in a unified framework for human-robot collaboration. The project addresses this challenge by developing a new systematic Bi-Trust framework to integrate humans’ trust in robots and robots’ trust in humans into the human-robot collaboration process. With the established Bi-Trust framework, a trust-level-based computational collaboration model is created to optimize and plan robot actions. The proposed approaches will reduce uncertain failures and improve the collaboration-quality of human-robot shared tasks.The goal of this project is to develop a systematic Bi-Trust framework for human-robot teams and create new computational models of trust dynamics and trust-level-based collaboration in order to enhance the human-robot partnership. The proposed research activities include: (1) investigating the factors that affect humans’ trust in robots and analyzing humans’ trust using multimodal physical and physiological data; (2) developing a new Bi-Trust framework entailing computational human-trusting-robot model and robot-trusting-human model for human-robot teams and establishing a computational human-robot collaboration model via the trust-local-maximum method; and (3) applying the Bi-Trust framework in real-world human-robot collaborative contexts and assessing its effectiveness. The findings of this project will improve the collaboration-quality for human-robot teams in collaborative contexts such as the new generation of smart manufacturing and potentially benefit the national economic growth by fostering increasing robotics and AI workforce.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.

协作机器人已被广泛用于在越来越多的领域中协助人类。正如人与人之间的协作一样，人与机器人之间的信任也具有双向性。然而，很少有人在一个统一的框架下对人-机器人信任问题和机器人-人信任问题进行研究。该项目通过开发一个新的系统化Bi-Trust框架来解决这一挑战，将人类对机器人的信任和机器人对人类的信任整合到人机协作过程中。在此基础上，建立了基于信任度的计算协作模型，用于机器人动作的优化和规划。本项目的目标是建立一个系统化的人-机器人协作的双信任框架，并建立新的信任动态计算模型和基于信任水平的协作模型，以增强人-机器人协作关系。研究内容包括：（1）研究影响人对机器人信任的因素，并利用多模态物理和生理数据分析人对机器人的信任：（2）提出一种新的人-机器人信任模型和机器人-人信任模型，并利用信任局部最大值方法建立人-机器人协作模型;以及（3）将双信任框架应用于现实世界的人机协作环境中，并评估其有效性。该项目的研究成果将在新一代智能制造等协作环境中提高人机团队的协作质量，并通过培养越来越多的机器人和人工智能劳动力，为国家经济增长带来潜在利益。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值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

Can Robots Get Some Human Rights? A Cross-Disciplinary Discussion

机器人能获得一些人权吗？

• DOI: 10.1155/2021/5461703
• 发表时间: 2021
• 期刊: Journal of Robotics
• 影响因子: 1.8
• 作者: Persaud, Priya;Varde, Aparna S.;Wang, Weitian
• 通讯作者: Wang, Weitian

A Digital Human System with Realistic Facial Expressions for Friendly Human-Machine Interaction

具有逼真面部表情的数字人体系统，可实现友好的人机交互

• 发表时间: 2023
• 期刊: The 2023 International Conference on Intelligent Computing
• 作者: Condegni, Anthony;Wang, Weitian;Li, Rui
• 通讯作者: Li, Rui

Reasoning the Trust of Humans in Robots through Physiological Biometrics in Human-Robot Collaborative Contexts

• DOI: 10.1109/urtc56832.2022.10002210
• 发表时间: 2022-09
• 期刊: 2022 IEEE MIT Undergraduate Research Technology Conference (URTC)
• 作者: Tiffany Guo;Omar Obidat;Laury Rodriguez;Jesse Parron;Weitian Wang

A Trust-Assist Framework for Human–Robot Co-Carry Tasks

人类与机器人共同执行任务的信任辅助框架

• DOI: 10.3390/robotics12020030
• 发表时间: 2023
• 期刊: Robotics
• 影响因子: 3.7
• 作者: Hannum, Corey;Li, Rui;Wang, Weitian
• 通讯作者: Wang, Weitian

Augmenting the Communication Naturalness via A 3D Audio-Visual Virtual Agent for Collaborative Robots

通过协作机器人的 3D 视听虚拟代理增强沟通自然度

• DOI: 10.1109/bigdata52589.2021.9671664
• 发表时间: 2021
• 期刊: 2021 IEEE International Conference on Big Data (Big Data
• 作者: Li, Rui;Wang, Weitian
• 通讯作者: Wang, Weitian