课题基金 / 基金详情

EAGER: Ensemble Design of Resource-Aware Control Strategies for Multi-Agent Robotic Systems

EAGER: Ensemble Design of Resource-Aware Control Strategies for Multi-Agent Robotic Systems
EAGER:多智能体机器人系统资源感知控制策略的集成设计
批准号:
1143941
负责人:
Mongying Hsieh
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-15 至 2014-06-30

项目摘要

项目成果

Mongying Hsieh的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
This project, generalizing mean-field approaches from physics and chemistry for integrated design of scalable, network resource aware, distributed control strategies for multi-agent robotic systems, aims to develop macroscopic models that retain salient features of the underlying multi-agent robotic system and use these models in the design of distributed control strategies. For complex cyber physical systems, this promises to provide a novel design methodology that is potentially applicable to a large class of systems and, therefore, will result in foundational knowledge of use to the community at large. This high-risk, high-reward project integrates ideas from physics, chemistry, control theory, and robotics to develop new theoretical foundations for the design, validation, and improvement of coordination strategies for multi-agent robotic systems.The project?s intellectual merit lies in the ensemble approach towards the design, validation, and improvement of cyber physical systems. Mean-field methods provide a system-level abstraction of the underlying distributed system while retaining the salient features of the various agent-level interactions. The generalization of these models to ensembles of interacting engineered systems provides new methods for designing distributed controllers that are sensitive to changing network resources and whose performance can be predicted and adjusted to achieve both the desired short-term and long-term performance specifications.Broader Impacts: The broader impacts of this project are twofold. First, the mean-field approach takes into account network resource usage and management, providing an integrated strategy for designing scalable decentralized control and coordination strategies. Second, different from biologically-inspired approaches, the mean-field approach enables the design of distributed coordination strategies whose performance can be systematically predicted and tuned to meet detailed performance specifications. This has the potential to unify various existing multi-agent coordination approaches. The research outcomes will be disseminated through publications in technical conferences and journals and incorporated into the PI?s existing undergraduate and graduate curriculum and K-12 outreach efforts targeted at increasing female participation in STEM fields.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Phase II IUCRC University of Pennsylvania: Center for Robots & Sensors for the Human Well-Being
  • 批准号:
    1939132
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2020
  • 负责人:
    Mongying Hsieh
  • 依托单位:
RI: Small: Collaborative Research: Extracting Dynamics from Limited Data for Modeling and Control of Unmanned Autonomous Systems
  • 批准号:
    1910308
  • 项目类别:
    Standard Grant
  • 资助金额:
    $23.0万
  • 财政年份:
    2019
  • 负责人:
    Mongying Hsieh
  • 依托单位:
CAREER: A New Paradigm in Control and Coordination of Robot Teams in Geophysical Flows
  • 批准号:
    1923940
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.68万
  • 财政年份:
    2018
  • 负责人:
    Mongying Hsieh
  • 依托单位:
Collaborative Research: FW-HTF: Integrating Cognitive Science and Intelligent Systems to Enhance Geoscience Practice
  • 批准号:
    1839686
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2018
  • 负责人:
    Mongying Hsieh
  • 依托单位:
海外基金