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.

该项目的主要目的是开发一种系统的方法，用于针对大型移动代理网络的一类动态的基于任务的运动协调问题设计可扩展，健壮和自适应算法的设计。代理在其运动上受到差异和代数约束的约束，包括非全面动力学和避免碰撞。任务是由外部来源随着时间的流逝而生成的，该任务是建模为随机过程或对抗过程，独立于代理的运动起作用。该项目将旨在精确表征闭环性能和算法的实现复杂性。 尽管所考虑的问题类别属于具有不确定信息的随机和组合决策系统的类别，但通过明确解决对代理，信息交换和局部环境感应的运动的差异和代数约束，将几何组分添加到这些问题中。所提出的方法是基于工具的开发，结合​​了系统和控制，机器人技术，组合优化和分布式计算。本项目解决了可能大量移动试剂的运动问题，以实现在感兴趣的地理扩展区域的动态变化任务。例如，代理可以代表收集有关时变空间场（例如温度概况，化学浓度等）的信息所需的移动传感器，或者移动继电器可在感兴趣的地区提供无线通信服务。该项目的成功完成将有助于开发具有功能的移动机器人网络，远远超出了当前技术的功能，并精确地了解网络的大小如何影响其性能及其复杂性。可能有可能是大型移动代理网络的可用性，能够在扩大空间上收集和传播信息将极大地影响我们在应用领域的能力，例如环境监测，行星勘探，搜索和救援，交通拥堵管理，监视，灾难管理和国家安全。