Collaborative Research: Dynamic Task-Based Coordination of Large-Scale Mobile Robotic Networks

协作研究：大规模移动机器人网络的动态任务协调

• 批准号: 0625635
• 负责人: Munther Dahleh
• 金额: $ 12万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-10-01 至 2009-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0625635&HistoricalAwards=false
• 关键词: Collaborative; Research; Dynamic; Task; Based

The main objective of this project is the development of a systematic approach to the design of scalable, robust, and adaptive algorithms for a class of dynamic task-based motion coordination problems for large-scale networks of mobile agents. The agents are subject to differential and algebraic constraints on their motion including, for example, non-holonomic dynamics and collision avoidance. Tasks are generated over time by an external source, modeled either as a stochastic or adversarial process, acting independently from the agents' motion. The project will aim at a precise characterization of the closed-loop performance and of the implementation complexity of the algorithms. While the class of problems under consideration falls within the class of stochastic and combinatorial decision systems with uncertain information, a geometric component is added to these problems by explicitly addressing differential and algebraic constraints on the motion of the agents, information exchange, and local sensing of the environment. The proposed approach is based the development of tools combining ideas from systems and control, robotics, combinatorial optimization, and distributed computing.This project addresses the problem of coordinating the motion of a possibly large number of mobile agents, in order to achieve dynamically-changing tasks over a geographically extended region of interest. For example, agents can represent mobile sensors required to collect information about a time-varying spatial field (e.g., temperature profiles, chemical concentration, etc.), or mobile relays providing wireless communication services over a region of interest. The successful completion of this project will facilitate the development of mobile robotic networks with capabilities that are well beyond those offered by current technology, with a precise understanding of how the size of the network affects its performance and its complexity. The availability of possibly large networks of mobile agents, able to collect and disseminate information over an extended volume of space will greatly impact our capabilities in application areas such as environmental monitoring, planetary exploration, search and rescue, traffic congestion management, surveillance, disaster management and national security.

这个项目的主要目标是开发一个系统的方法来设计可扩展的，强大的，和自适应算法的一类动态的基于任务的运动协调问题的大规模网络的移动的代理。代理受到微分和代数约束，他们的运动，包括，例如，非完整动力学和碰撞避免。任务由外部源随时间生成，建模为随机或对抗过程，独立于代理的运动。该项目的目标是精确表征闭环性能和算法的实现复杂性。 虽然类的问题正在考虑福尔斯类的随机和组合决策系统的不确定信息，几何组件添加到这些问题，明确解决微分和代数约束的运动的代理，信息交换，和当地的环境传感。所提出的方法是基于开发的工具相结合的想法，从系统和控制，机器人技术，组合优化，和分布式computing.This项目解决的问题，协调运动的可能大量的移动的代理，以实现动态变化的任务在地理上扩展的区域感兴趣。例如，代理可以表示收集关于时变空间场的信息所需的移动的传感器（例如，温度曲线、化学浓度等），或在感兴趣的区域上提供无线通信服务的移动的中继。该项目的成功完成将促进移动的机器人网络的发展，其能力远远超出当前技术所提供的能力，并准确了解网络的规模如何影响其性能和复杂性。能够在更大空间范围内收集和传播信息的可能大型移动的代理网络的存在将极大地影响我们在环境监测、行星探索、搜索和救援、交通拥堵管理、监视、灾害管理和国家安全等应用领域的能力。