CAREER: Secure, Resilient, and Risk-Aware Multi-Robot Coordination

该项目的首要目标是使多机器人系统在现实世界条件下可靠地运行。目前大多数多机器人系统都是“脆弱的”，因为单个机器人的故障可能会导致整个团队的崩溃。使机器人丧失能力或损害其传感器的网络攻击正变得越来越现实。该项目将专注于机器人在易发生故障或对抗性环境中操作的多机器人协调。该项目将解决的关键问题是，一组机器人如何仔细协调和调整它们的行动，使它们对失败具有弹性。该项目的成果将是朝着在现实世界条件下持续可靠的自主操作的总体愿景迈出的重要一步。这些研究活动将与教育和推广活动齐头并进，这些活动将整合精准农业和环境监测中多机器人协调的真实例子，以培养下一代工程师的多学科思维。为了扩大代表性不足的少数民族的参与，该项目将为中学生开发一个新的动手机器人编程夏令营。为确保广泛适用，将在该讲习班上对中学教师进行培训，目标是使他们将技术活动纳入课堂。研究人员将开发一个新的多机器人协调课程，并指导未来的教师，即本科生/研究生，通过学生发起的课程计划创建和领导一个新的设计导向课程。我们的研究成果将通过研讨会、面向更广泛受众的文章和社区外展活动进行传播。该项目的主要智力贡献是引入一类新的问题，并开发新的算法和理论限制，用于对抗和不确定环境中的多机器人协调。底层框架将基于子模块优化，这是一种经常使用的多机器人协调技术。现有的作品，使用子模块优化协调通常假设的功能值可以精确计算。该项目的主要贡献将是放松这一假设，这将导致各种各样的研究问题，将被调查。从广义上讲，将研究三类问题：设计离线协调部署，以防止对抗性攻击;设计在线自适应策略，以适应实时故障和攻击;以及设计在线和离线计划，考虑到随机子模块优化中的新风险度量。将研究问题的各种版本，例如：分布式和可扩展性;更丰富的攻击模型，特别是分布式网络;更丰富的效用函数，特别是使用深度神经网络的效用函数。该项目旨在设计具有恒定因子近似和恒定竞争比保证的算法。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The overarching goal of this project is to make multi-robot systems operate reliably in real-world conditions. Most current multi-robot systems are "brittle" since the failure of a single robot may bring the whole team down. Cyber-attacks that incapacitate robots or compromise their sensors are becoming increasingly realistic. This project will focus on multi-robot coordination in scenarios where the robots operate in failure-prone or adversarial environments. The key question that the project will address is how can a team of robots carefully coordinate and adapt their actions to make them resilient to failures. The outcomes of this project will be a significant step towards the overarching vision of persistent and reliable autonomous operations in real-world conditions. These research activities will go hand-in-hand with educational and outreach activities that will integrate real-world examples of multi-robot coordination in precision agriculture and environmental monitoring to train the next generation of engineers in multi-disciplinary thinking. To broaden participation from underrepresented minorities, the project will develop a new hands-on robot programming summer camp for middle-school students. To ensure broad applicability, middle-school teachers will be trained in this workshop with the goal of them incorporating the technical activities in their classrooms. The investigator will develop a new course on multi-robot coordination and mentor undergraduate/graduate students, who are the future faculty, to create and lead a new design-oriented course through the Student Initiated Courses program. Dissemination of our findings will be achieved through workshops, articles geared toward broader audiences, and community outreach events.The main intellectual contributions of this project are in the introduction of a novel class of problems and development of new algorithms and theoretical limits for multi-robot coordination in adversarial and uncertain settings. The underlying framework will be based on submodular optimization which is an often-used technique in multi-robot coordination. Existing works that use submodular optimization for coordination typically assume that the function value can be computed exactly. The key contribution of this project will be to relax this assumption which leads to a wide variety of research problems that will be investigated. Broadly speaking, three classes of problems will be investigated: devising offline coordinated deployments that are secure against adversarial attacks; devising online, adaptive strategies that are resilient to real-time failures and attacks; and devising online and offline plans that take into account novel measures of risk in stochastic submodular optimization. Various versions of the problem such as: distributed and scalable; richer attack models particularly for distributed networks; and richer utility functions particularly those using deep neural networks, will be investigated. The project seeks to devise algorithms with constant factor approximation and constant competitive ratio guarantees.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.