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Collaborative Proposal: EMT/MISC Behavior Based Molecular Robotics

Collaborative Proposal: EMT/MISC Behavior Based Molecular Robotics
合作提案:基于 EMT/MISC 行为的分子机器人
批准号:
0829685
负责人:
Hao Yan
金额:
$42.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2008
资助国家:
美国
项目状态:
已结题
起止时间:
2008-09-01 至 2012-08-31

项目摘要

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中文摘要
翻译
基于行为的机器人技术是围绕这样一个理念建立起来的:机器人可以通过连接基本的传感器和执行器模块来构建,而不需要形成它们运行的世界的任何内部表征。如果设计得当,这样的机器人,无论是作为个体还是作为群体,都表现出复杂和看似“智能”的一面。行为,实时解决具有挑战性的任务,同时只对当地环境做出反应并遵守当地规则。在某种程度上,这种机器人方法的灵感来自于考虑自然系统,比如群居昆虫在其群体中的自组织和适应性。类似的方法将在未来三年内启动基于行为的分子机器人领域的发展,导致分子组在观察者看来表现出各种任务导向的行为或某种形式的有目的和动态的自组织。基于个体行为的分子机器人是显示多个传感器-致动器的单个分子。当暴露在人工景观中,显示与传感器致动器相关的基质时,分子开始执行基本步骤,在随机意义上,由它们不断变化的局部环境决定。在一些被称为规范的场景中,个体分子机器人和它们的集体将执行算法,模仿带有序列控制机制的上紧发条自动机。相比之下,在不确定的环境中,机器人和它们的集体将展示来自单个传感器和执行器的内部组织以及分子与其环境之间的局部相互作用的特性。重要的是,这些对分子行为的新解释将允许与之前所有分子机器人方法完全不同的实验,同时保持实验设计的现实性,从而实现在物理世界中的体现。
英文摘要
Behavior-based robotics was established around the idea that robots could be constructed by connecting elementary sensor and actuator modules, without the need to form any internal representation of the world in which they operate. When designed appropriately, such robots, both as individuals and as groups, exhibit complex and seemingly ?intelligent? behaviors, solving challenging tasks in real time, while reacting only to their local environment and obeying sets of local rules. In part, this approach to robotics was inspired by considering natural systems, such as self-organization and adaptability of social insects in their colonies. An analogous approach to initiate the development of the field of behavior-based molecular robotics will be performed over the next three years, leading to groups of molecules that would appear to an observer to show a variety of task-oriented behaviors or some form of purposeful and dynamic self-organization. Individual behavior-based molecular robots are single molecules displaying multiple sensors-actuators. When exposed to artificial landscapes displaying substrates keyed to their sensors-actuators, the molecules start executing elementary steps, determined, in a stochastic sense, by their constantly changing local environments. On some landscapes, called prescriptive, individual molecular robots and their collectives will execute algorithms mimicking wound-up automata with sequence control mechanisms. In contrast, on non-deterministic landscapes, the robots and their collectives will demonstrate properties emerging from internal organization of individual sensors and actuators and through local interactions between molecules and their environments. Importantly, these new interpretations of molecular behaviors will allow radically different experiments from all previous approaches to molecular robotics, while keeping experimental designs realistic, leading to embodiment in the physical world.
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Collaborative Research: Multi-Agent Adaptive Data Collection for Automated Post-Disaster Rapid Damage Assessment
  • 批准号:
    2316654
  • 项目类别:
    Standard Grant
  • 资助金额:
    $16.5万
  • 财政年份:
    2023
  • 负责人:
    Hao Yan
  • 依托单位:
Self-assembled DNA crystals as scaffolds for macromolecules
  • 批准号:
    2324944
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2023
  • 负责人:
    Hao Yan
  • 依托单位:
SemiSynBio-III: DNA Templated Chiral Metamaterials for Information Storage
  • 批准号:
    2227650
  • 项目类别:
    Standard Grant
  • 资助金额:
    $150.0万
  • 财政年份:
    2022
  • 负责人:
    Hao Yan
  • 依托单位:
Rational design of self-assembled, three-dimensional DNA crystals
  • 批准号:
    2004250
  • 项目类别:
    Standard Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2020
  • 负责人:
    Hao Yan
  • 依托单位:
海外基金