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EAGER: CNS: Misdirection in Robot Teams: Exploiting Organizational Principles for Operational Advantage

EAGER：CNS：机器人团队的误导：利用组织原则获得运营优势

基本信息

批准号：
1848653
负责人：
Ronald Arkin
金额：
$ 27.19万
依托单位：
Georgia Tech Research Corporation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-10-01 至 2021-03-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1848653&HistoricalAwards=false
关键词：
EAGER CNS Misdirection Robot Teams

项目摘要

Trust, dependability, cohesion, and capability are integral to an effective team. These attributes are the same for teams of collaborating robots and humans as well as all-robot teams. For a team to remain effective in the presence of faults, failures, and errors from nature or intent, team members must have sufficient perception and understanding of the problem and possible solutions to make appropriate adjustments in their operations. When multiple teams with competing incentives are tasked, a strategy, if available, may be to weaken, influence or sway the attributes of other teams and limit their understanding of their full range of options. Such strategies are widely found, for example, in nature, sporting contests, and military operations, where strategies such as feints and misdirection often appear. This project focuses on one class of higher-level strategies for multi-robots: namely, to misdirect and where feasible to counter misdirection. As multi-robot systems become more autonomous, distributed, networked, numerous, and with more capability to make critical decisions, the prospect for intentional and unintentional misdirection must be anticipated. This project will support robust multi-robotic operations in important strategic domains such as security and military operations. The project studies strategies to enable co-robots, multi-robots and teams of multi-robots to model, generate, and cope with misdirection in various situations. This research direction in robotic control offers a novel approach to resilience in and among these teams to these forms of possible disruption. Computational models, drawn particularly from studies of human endeavors and group behaviors, provide a general framework for understanding, producing, and countering misdirection in robotic systems. A framework of computational models will be designed using recursive schema-theoretic models of behaviors at the individual and team levels, building on decentralized methods of control and communication, to provide robustness in the presence of noisy and chaotic environments.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.

信任、可靠性、凝聚力和能力是高效团队的组成部分。这些属性对于机器人和人类协作团队以及全机器人团队来说是相同的。为了使团队在出现自然或故意的故障、故障和错误时保持高效，团队成员必须对问题和可能的解决方案有足够的认识和理解，以便在操作中做出适当的调整。当多个具有竞争性激励的团队承担任务时，如果可行的话，策略可能是削弱、影响或动摇其他团队的属性，并限制他们对其全部选项的理解。此类策略广泛存在，例如在自然界、体育比赛和军事行动中，经常出现佯攻和误导等策略。该项目重点关注多机器人的一类高级策略：即误导以及在可行的情况下对抗误导。随着多机器人系统变得更加自主、分布式、网络化、数量众多，并且具有更强的做出关键决策的能力，必须预见到有意和无意的误导的可能性。该项目将支持安全和军事行动等重要战略领域的强大多机器人行动。该项目研究了使协作机器人、多机器人和多机器人团队能够在各种情况下建模、生成和应对误导的策略。机器人控制的这一研究方向为这些团队内部和之间的这些可能的破坏形式的恢复提供了一种新颖的方法。计算模型特别来自对人类努力和群体行为的研究，为理解、产生和对抗机器人系统中的误导提供了一个通用框架。将使用个人和团队层面的递归模式理论模型来设计计算模型框架，建立在分散的控制和通信方法的基础上，以在嘈杂和混乱的环境中提供鲁棒性。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

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Misdirection in Robot Teams: Methods and Ethical Considerations

机器人团队的误导：方法和道德考虑

DOI：
发表时间：
2019
期刊：
2019 International Association for Computing and Philosophy annual conference
影响因子：
0
作者：
Arkin, Ronald C.
通讯作者：
Arkin, Ronald C.

Counter-Misdirection in Behavior-Based Multi-Robot Teams

基于行为的多机器人团队中的反误导

DOI：
发表时间：
2021
期刊：
2021 IEEE International Conference on Intelligence and Safety for Robotics
影响因子：
0
作者：
Chen, Shengkang;Arkin, Ronald C.
通讯作者：
Arkin, Ronald C.

Misdirection in Robot Teams: Methods and Ethical Considerations (Extended Abstract)

机器人团队的误导：方法和道德考虑（扩展摘要）

DOI：
发表时间：
2020
期刊：
2019 Conference of the International Association for Computing and Philosophy (IACAP 2019
影响因子：
0
作者：
Arkin, Ronald C
通讯作者：
Arkin, Ronald C

Push and Pull: Shepherding Multi-Agent Robot Teams in Adversarial Situations

DOI：
10.1109/arso46408.2019.8948797
发表时间：
2019-10
期刊：
2019 IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO)
影响因子：
0
作者：
Michael J. Pettinati;R. Arkin
通讯作者：
Michael J. Pettinati;R. Arkin