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

NSF-CONACYT 合作研究：自主机器人的搜索、监视和追踪

• 批准号: 0725444
• 负责人: Seth Hutchinson
• 金额: $ 10万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2010-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0725444&HistoricalAwards=false
• 关键词: NSF; CONACYT; Collaborative; Research; Search

(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.

(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。 该研究的目标是开发规划和控制算法的传感器能力有限或受约束的系统，设计运动策略，考虑到几何，运动学和动态约束，并了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之前的工作来处理3D环境中的几何约束（即，世界上存在障碍物），以及对追踪者运动的运动学和动力学约束;设计、形式验证和实现用于反应运动规划的机器人体系结构;以及使用真实的机器人系统测试该方法。(2)更广泛的意义：机器人技术有望对社会产生广泛的影响，拟议的研究有可能为当今感兴趣的许多问题提供解决方案。 这些包括救灾、搜索和救援、科学研究（例如，北极、海底或行星探索）。此外，将开发的基本数学工具可以在通信，经济和其他领域中找到应用程序，其中不确定性是相关的decisionmaking.The拟议的研究的具体重点是在传感器为基础的机器人的传感，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沿着与规则，可以用来切换这些策略的基础上传感器输入。 由于系统必须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件，可以严格表征系统性能，包括稳定性和收敛性。