Engineering Resilient Swarm Robotics Systems

多机器人系统(也称为蜂群)正在变得无处不在。尽管最近的技术进步显示了它们在运输、制造、医疗系统和灾难应对方面的潜力，但必须应对许多挑战，才能安全地实现它们的潜力。例如，在2016年麦克默里堡野火期间，一群具有不同能力(例如飞行和驾驶)的机器人本可以被用来评估灾难的规模，定位处于危险中的人，并为应急人员提供强大的通信网络。不幸的是，这些功能在目前的技术下是不可能实现的；如何设计集体行为并确保机器人群体的安全和弹性，特别是在具有挑战性和不可预测的现实世界条件下，是有待解决的研究问题。 机器人学、人工智能和物联网正在推动科技领域当前的研究，而多机器人系统是主要课题之一。然而，当前关键系统(例如工业和航空航天)的软件标准不能直接适用于呈现涌现的分布式系统，即从单个机器人的代码中看不到的集体行为。我们认为，在开发过程中检测和纠正特定于紧急系统的问题应该是系统设计的一个组成部分。此外，我们考虑如何在执行任务期间更新群体的行为和目标，以适应环境或优先事项的变化。 在本研究计划中，我们建议通过三条研究路线来解决这些问题： 目标i)在机器人群体中设计有弹性的集体行为：我们将定义允许群体感知问题并适当适应的理论基础； 目标二)在Buzz编程语言中嵌入安全原语：我们将在开发阶段验证集体系统的安全属性 目标三)为大型机器人团队制定软件管理战略：我们将研究部署和发布软件修订版到已部署的机器人网络的新方法，考虑到它们在移动性和资源方面的非常特殊的要求 总体而言，这项研究将导致集群机器人的实际应用。我们设想灾难应对(在麦克默里堡火灾等情况下)是我们系统的第一次演示，在那里部署机器人并提供持续的情况监测，协助受害者搜索，并以完全自主、自适应的方式提供通信基础设施，人类监督最少。

Multi-robot systems (a.k.a. swarms') are becoming pervasive. Although recent technological advancements demonstrate their potential in transportation, manufacturing, medical systems, and disaster response, numerous challenges must be addressed to safely realize their potential. During the 2016 Fort McMurray wildfire, for example, a swarm of robots with heterogeneous capability (e.g. flying vs. driving) could have been used to assess the scale of the disaster, locate people in danger, and provide a robust communication network for responders. Unfortunately, these functions are not possible with current technology; how to engineer collective behavior and assure safety and resilience of robot swarms, particularly in challenging and unpredictable real-world conditions, are open research problems. Robotics, artificial intelligence, and the Internet-of-Things are driving current research for the technology sector, and multi-robot systems are one of the main topics. However, current software standards for critical systems (e.g. industrial and aerospace) are not directly applicable to distributed systems which exhibit emergence i.e. collective behaviour that is not apparent from a single robot's code. We believe that detecting and correcting issues specific to emergent systems during development should be an integral part of system design. Furthermore, we consider how swarms' behaviour and goals could be updated during missions to adapt to changes in the environment or priorities. In this research program, we propose to address these issues along 3 lines of research: Aim I) Engineer resilient collective behavior in robot swarms: we will define the theoretical foundations that allow swarms to perceive problems and adapt appropriately; Aim II) Embed safety primitives in the Buzz programming language: we will verify safety properties of collective systems during the development phase Aim III) Develop software management strategies for large robot teams: we will study novel methods for deploying and releasing software revisions to deployed robotic networks, considering their very peculiar requirements in terms of mobility and resources Overall, this research will lead to practical swarm-robotics applications. We envision disaster response (in situations such as the Fort McMurray fire) as a first demonstration of our systems, where robots are deployed and provide constant situation monitoring, assist in victim search, and provide a communication infrastructure in a fully-autonomous, self-adaptive way, with minimal human supervision.