CAREER: Modeling and Design of Composite Swarming Behaviors
职业:复合群体行为的建模和设计
基本信息
- 批准号:1150223
- 负责人:
- 金额:$ 50.17万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-03-01 至 2018-02-28
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This project, developing models for complex swarming behaviors by incrementally starting from the properties of an individual agent, which includes noisy sensors and actuators and stochastic behavior, and validating the models by systematic experimentation with physical systems, will bridge the gap between analysis by simple primitives and their composition into complex swarming behaviors. Specifically, this research will consist of a comprehensive study of containment, partitioning, and re-configuration swarming primitives, and then show how they can be composed into complex swarming behaviors such as pattern recognition, sensor-based motion, and adaptive shape change. These primitives and behaviors have been chosen because they challenge existing modeling approaches and lead to independent contributions addressing grand challenge applications by themselves.Inspired by the robust and scalable operation of bees, termites, ants and multi-cellular organisms, the funding of this proposed work will lead to a methodology to compose stochastic swarming behaviors in a principled way using probabilistic models. These models will be grounded in the probabilistic behavior of an individual agent's sensing, actuation, communication and computational properties by modeling the system at multiple levels of abstraction going back and forth from physical experimentation, kinematic models, and stochastic simulations to macroscopic difference equations. By grounding the models in physical experiments, models will be able to serve as design tool for not only the computational, but also the physical properties of an individual agent.Broader Impacts: A principled methodology for modeling and designing swarming systems will create the foundation for designing and deploying swarm robotic systems for search and rescue, environmental response, precision agriculture, and surveillance, among others. At the same time, the ability to design swarms might also shed light on the workings of biological and chemical systems, such as social insects, multi-cellular systems, and self-assembly, enabling the design of complex multi-cellular systems with arbitrary functionality. Finally, algorithms and systems resulting from this research lend themselves to artistic installations, drawing a broad public into the fascination of swarming systems and nurture an understanding for the distributed nature that is common to all living systems. The proposed research will be deeply integrated with education. Specific offerings developed in this integrated research and education plan include: a modular robotic activity that introduces computational thinking to 4th graders, a crash-course on embedded systems geared at 1st year students from under-represented groups, a comprehensive robotics curriculum for upperclassmen, and an interdisciplinary graduate seminar on "Swarm Intelligence" and "Self-Assembly" that will actively involve students from other disciplines and encourage them to apply the proposed multi-level modeling methodology to their research.
该项目通过从个体代理的属性(包括噪声传感器和致动器以及随机行为)逐步开始开发复杂群集行为的模型,并通过物理系统的系统实验验证模型,将弥合简单原语分析与其组成复杂群集行为之间的差距。具体来说,这项研究将包括一个全面的研究包容,分区和重新配置群集原语,然后展示他们如何可以组成复杂的群集行为,如模式识别,基于传感器的运动,和自适应形状变化。这些原语和行为已被选中,因为他们挑战现有的建模方法,并导致独立的贡献解决大挑战applications.Inspired蜜蜂,白蚁,蚂蚁和多细胞生物体的强大和可扩展的操作,这项拟议工作的资金将导致一种方法来组成随机群集行为的原则性的方式使用概率模型。这些模型将通过在从物理实验、运动学模型和随机模拟到宏观差分方程的多个抽象层次上对系统进行建模,以单个代理的感知、驱动、通信和计算属性的概率行为为基础。通过将模型建立在物理实验的基础上,模型不仅可以作为计算工具,还可以作为单个智能体的物理属性的设计工具。更广泛的影响:一种建模和设计群集系统的原则性方法将为设计和部署群集机器人系统奠定基础,用于搜索和救援,环境响应,精准农业和监视等。与此同时,设计群体的能力也可能揭示生物和化学系统的运作,如社会昆虫,多细胞系统和自组装,使设计具有任意功能的复杂多细胞系统成为可能。最后,从这项研究中产生的算法和系统适合于艺术装置,吸引广大公众进入群集系统的魅力,并培养对所有生命系统共同的分布式性质的理解。该研究将与教育深度融合。在这个综合研究和教育计划中开发的具体产品包括:一个模块化的机器人活动,介绍了计算思维的四年级学生,嵌入式系统的速成课程,面向一年级学生从代表性不足的群体,一个全面的机器人课程高年级,以及一个关于“群体智能”和“自我组装”的跨学科研究生研讨会这将积极吸引其他学科的学生参与,并鼓励他们将拟议的多层次建模方法应用于他们的研究。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nicolaus Correll其他文献
Nicolaus Correll的其他文献
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{{ truncateString('Nicolaus Correll', 18)}}的其他基金
SBIR Phase II: Gripper-integrated proximity, contact and force sensing for collaborative robots
SBIR 第二阶段:协作机器人的夹具集成接近、接触和力传感
- 批准号:
1853146 - 财政年份:2019
- 资助金额:
$ 50.17万 - 项目类别:
Standard Grant
SBIR Phase I: Whole-body 3D perception for human-safe collaborative robots
SBIR 第一阶段:人体安全协作机器人的全身 3D 感知
- 批准号:
1843188 - 财政年份:2019
- 资助金额:
$ 50.17万 - 项目类别:
Standard Grant
SBIR Phase I: Gripper-integrated proximity, contact and force sensing for collaborative robots
SBIR 第一阶段:协作机器人的夹具集成接近、接触和力传感
- 批准号:
1746003 - 财政年份:2018
- 资助金额:
$ 50.17万 - 项目类别:
Standard Grant
EAGER: Centralized Control of Large-Scale Distributed Sensor/Actuator Networks: Self-organizing Amorphous Facades
EAGER:大规模分布式传感器/执行器网络的集中控制:自组织非晶立面
- 批准号:
1153158 - 财政年份:2012
- 资助金额:
$ 50.17万 - 项目类别:
Standard Grant
NRI-Large: Collaborative Research: Soft Compliant Robotic Augmentation for Human-Robot Teams
NRI-Large:协作研究:人机团队的软兼容机器人增强
- 批准号:
1225934 - 财政年份:2012
- 资助金额:
$ 50.17万 - 项目类别:
Continuing Grant
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