CPS: TTP Option: Synergy: Collaborative Research: Dependable Multi-Robot Cooperative Tasking in Uncertain and Dynamic Environments

在民用和军事应用的推动下，如协调监视、搜索和救援、水下或空间探索、危险环境中的操作和快速应急响应，机器人团队的合作行动已成为一个重要的研究领域。然而，这种机器人团队的协调策略在很大程度上仍然是通过试错过程来开发的。因此，这些战略不能保证任务的成功。该奖项支持基础研究，为保证任务成功的多机器人系统提供可证明正确的正式设计理论。此外，研究结果可以扩展到由分布式和协调子系统组成的更通用的网络物理系统（cps）的设计，如国家电网、地面/空中交通网络和制造系统。这些cps是国家民用基础设施的关键组成部分，必须可靠地运行以确保公共安全。所采取的多学科方法将有助于扩大代表性不足的群体在研究中的参与，并对工程教育产生积极影响。关注多机器人团队，研究的目标是为cps的可证明正确的形式化设计理论建立基础。该设计理论通过设计局部协调规则和控制律来保证多机器人团队具有给定的全局性能。其基本思想是将团队任务分解为单独的子任务，这样设计就可以简化为单个机器人的局部综合问题。结合混合系统、监督控制、常规推理和模型检查的多学科方法将被用来实现这一目标。开发的理论将使团队中的机器人能够合作学习他们在任务中的个人角色，然后自动合成本地主管来完成他们的子任务。该方法的一个显著特点在于其处理环境不确定性和未建模动力学的能力，因为不需要每个代理/机器人的过渡动力学及其与环境的相互作用的显式模型。此外，该设计是在线的和反应性的，使机器人团队能够适应不断变化的环境和动态任务。衍生的理论将作为软件工具实施，并将通过由非结构化城市/农村地区的无人地面和空中车辆组成的真实机器人系统进行演示。

Driven by both civilian and military applications, such as coordinated surveillance, search and rescue, underwater or space exploration, manipulation in hazardous environments, and rapid emergency response, cooperative actions by teams of robots has emerged as an important research area. However, the coordination strategies for such robot teams are still developed to a great extent by trial-and-error processes. Hence, the strategies cannot guarantee mission success. This award supports fundamental research to provide a provably correct formal design theory of multi-robot systems that guarantees mission success. Furthermore, results from the research can be extended to the design of more general cyber-physical systems (CPSs) consisting of distributed and coordinated subsystems, such as the national power grid, ground/air traffic networks, and manufacturing systems. These CPSs are critical components of the national civil infrastructure that must operate reliably to ensure public safety. The multidisciplinary approach taken will help broaden participation of underrepresented groups in research and positively impact engineering education. Focusing on multi-robot teams, the goal of the research is to build foundations for a provably correct formal design theory for CPSs. This design theory will guarantee a given global performance of multi-robot teams through designing local coordination rules and control laws. The basic idea is to decompose the team mission into individual subtasks such that the design can be reduced to a local synthesis problem for individual robots. Multidisciplinary approaches combining hybrid systems, supervisory control, regular inference and model checking will be utilized to achieve this goal. The developed theory will enable robots in the team to cooperatively learn their individual roles in a mission, and then automatically synthesize local supervisors to fulfill their subtasks. A salient feature of this method lies on its ability to handle environmental uncertainties and unmodeled dynamics, as there is no need for an explicit model of the transition dynamics of each agent/robot and their interactions with the environment. In addition, the design is online and reactive, enabling the robot team to adapt to changing environments and dynamic tasking. The derived theory will be implemented as software tools and will be demonstrated through real robotic systems consisting of unmanned ground and aerial vehicles in unstructured urban/rural areas.