NSF-CONACYT Collaborative Research: Search, Surveillance, and Pursuit by Autonomous Robots

(1)技术描述：拟议的研究将集成控制、传感和规划，以开发能够有效执行搜索、监视和追捕的自主系统。该研究的目标是为传感器能力有限或受限的系统开发规划和控制算法，设计考虑几何、运动学和动态约束的运动策略，并理解和平衡所需算法的最优性和复杂性之间的权衡。这些目标将通过扩展先前的工作来实现，以处理3D环境中的几何约束（即，世界中存在障碍物），以及对追踪者运动的运动学和动力学约束；设计，正式验证和实现一个机器人体系结构的反应运动规划；并使用真实的机器人系统对该方法进行了测试。(2)更广泛的意义：机器人技术将对社会产生广泛的影响，提出的研究有可能为当今许多感兴趣的问题提供解决方案。其中包括救灾、搜索和救援、科学研究（如北极、海底或行星探测）。此外，将开发的基本数学工具可以应用于通信、经济和其他与决策有关的不确定性领域。提出的研究的具体重点是传感器机器人的传感，规划和控制的集成。所提出的方法假定规划系统的作用是自动构建反馈控制策略以及可用于根据传感器输入在这些策略之间切换的规则。由于系统必须在其中运行的世界的复杂性和不可预测性，因此需要进行规划和感知。使用反馈控制作为规划的基本构建块，可以严格描述系统性能，包括稳定性和收敛性。

(1) Technical Description:The proposed research will integrate control, sensing and planning to develop autonomous systems that can effectively perform search, surveillance, and pursuit. The goals of the research are to develop planning and control algorithms for systems with limited or constrained sensor capabilities, to design motion strategies that take account of geometric, kinematic, and dynamic constraints, and to understand and balance the trade-off between the optimality and complexity of the required algorithms. These goals will be achieved by extending previous work to deal with geometric constraints in 3D environments (i.e., the presence of obstacles in the world), and with and kinematic and dynamic constraints on pursuer motion; designing, formally verifying and implementing a robot architecture for reactive motion planning; and testing the approach using real robot systems.(2) Broader Significance:Robotics is poised to have broad impact on society, and the proposed research has the potential provide inroads to solutions for numerous problems that are of interest today. These include disaster relief, search and rescue, scientific studies (e.g., arctic, undersea or planetary exploration). In addition, the basic mathematical tools that will be developed could find applications in communications, economics and other domains in which uncertainty is relevant to decision making.The specific focus of the proposed research is on the integration of sensing, planning and control in sensor-based robotics. The proposed approach posits that the role of a planning system is to automatically construct feedback control policies along with rules that can be used to switch between these policies based on sensor input. The need for planning and sensing arises due to the complexity and unpredictability of the world in which the system must operate. The use of feedback control as the fundamental building block for planning allows rigorous characterization of system performance, including stability and convergence.