Collaborative Research: EMT/MISC: Behavior-Based Molecular Robotics

合作研究：EMT/MISC：基于行为的分子机器人

• 批准号: 0829579
• 负责人: Nils Walter
• 金额: $ 33万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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
• 起止时间: 2008-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0829579&HistoricalAwards=false
• 关键词: Collaborative; Research; EMT; MISC; Behavior

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.

基于行为的机器人技术是围绕这样的想法建立的：机器人可以通过连接基本传感器和执行器模块来构建，而不需要形成它们运行的​​世界的任何内部表示。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，都会表现出复杂且看似“智能”的特点。行为，实时解决具有挑战性的任务，同时仅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对自然系统的考虑，例如群居昆虫的自组织和适应性。未来三年将采用类似的方法来启动基于行为的分子机器人领域的发展，从而产生在观察者看来表现出各种面向任务的行为或某种形式的有目的的分子群。和动态自组织。基于个体行为的分子机器人是显示多个传感器-执行器的单分子。当暴露于显示与其传感器-执行器相连的基质的人造景观时，分子开始执行基本步骤，从随机意义上讲，这些步骤是由它们不断变化的局部环境决定的。在某些被称为规定性的环境中，单个分子机器人及其集体将执行具有序列控制机制的模仿上发条自动机的算法。相比之下，在非确定性景观中，机器人及其集体将展示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所产生的属性。重要的是，这些对分子行为的新解释将允许进行与之前所有分子机器人方法截然不同的实验，同时保持实验设计的现实性，从而在物理世界中得到体现。