AiTF: Collaborative Research: Distributed and Stochastic Algorithms for Active Matter: Theory and Practice

AiTF：协作研究：活跃物质的分布式随机算法：理论与实践

基本信息

批准号：
1733812
负责人：
Dana Randall
金额：
$ 40.8万
依托单位：
Georgia Tech Research Corporation
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-01 至 2022-12-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1733812&HistoricalAwards=false
关键词：
AiTF Collaborative Research Distributed Stochastic

项目摘要

Swarm robotics explores how groups of robots can work towards a singular goal, which is typically achieved by equipping each robot with sensory capabilities, basic computing power, and movement. The sensors detect and use information about the environment to decide on the next action. Swarm robotics has made many advances in recent years, but is still in its infancy. This project proposes to explore swarm robotics systems in a non-standard way as physical systems. The PIs take a "task-oriented" approach to develop the distributed algorithmic rules that the robots will run (at the microscopic level) in order to converge to the desired collective behavior (at the macroscopic level). This will provide understanding of the minimal requirements for individuals to accomplish the desired behavior, for both algorithmic and physical realizations, and will provide a more principled approach for studying swarm robotics. The robots envisioned are small in scale, ranging in size from millimeters to centimeters, so that when deployed in dense environments, they will behave as programmable active matter.The PIs have strong records for interdisciplinary research, including initiating interdisciplinary areas (e.g., robo-physics, self-organizing particle systems, and the fusion of statistical physics and randomized algorithms). They have a strong commitment toward supporting minorities, women, and undergrad research (e.g., through NSF REUs, including through this project, NSF S-STEM programs at ASU; ADVANCE and S.U.R.E. programs at Georgia Tech). Any breakthrough in this combination of swarm and active matter systems will require employing analyses and techniques from stochastic systems, condensed matter physics, swarm systems, robotics, and distributed algorithms to understand and achieve the desired group dynamics, and hence will bring together and educate researchers from different disciplines and specialties. New research approaches and findings will be incorporated into multiple graduate courses and workshops will provide tutorials for bridging multiple disciplines, making material accessible to young researchers and helping to widely disseminate results. Findings (including open source code) will be published in the various disciplines, and will be be made available on our web pages and ArXiv. The project explores the fundamentals of swarm robotics from a physics standpoint, by viewing the ensemble as active matter composed of programmable elements at the micro-level. The project will follow a (macro-)task oriented approach, and design a distributed stochastic algorithmic framework to design and evaluate algorithms at the micro-level that will yield the targeted emergent macroscopic behavior. The emergent behaviors it addresses include compression (maintaining coherence of a connected community while minimizing perimeter), bridging (connecting two or more locations in the most efficient manner), alignment (determining an agreed upon direction of orientation), jamming (obstruction of movement by increased collective flow), and locomotion (collectively moving while maintaining cohesiveness). Many of these have interesting converse problems which are also equally worthwhile, such as exploration (maintaining a connected population, but exploring maximal area) and non-alignment (representing a disordered ensemble). In some cases the collective behavior acts like a physical system changing between a liquid (disordered) and a solid (ordered) state, as determined by phase transitions in the systems. The project will explore stochastic and distributed algorithms for rigorously achieving these goals.

Swarm Robotics探索了机器人组如何朝着一个奇异的目标努力，通常通过为每个机器人配备感觉功能，基本计算能力和运动来实现。传感器检测并使用有关环境的信息来决定下一个动作。近年来，Swarm Robotics取得了许多进步，但仍处于起步阶段。该项目建议以非标准的方式探索群体机器人系统。 PI采用一种“面向任务”的方法来开发机器人将（在微观级别）运行的分布式算法规则，以收敛到所需的集体行为（在宏观级别上）。这将提供对个人完成所需行为（算法和物理实现）的最小要求的理解，并将为研究群体机器人技术提供更有原则的方法。 The robots envisioned are small in scale, ranging in size from millimeters to centimeters, so that when deployed in dense environments, they will behave as programmable active matter.The PIs have strong records for interdisciplinary research, including initiating interdisciplinary areas (e.g., robo-physics, self-organizing particle systems, and the fusion of statistical physics and randomized algorithms).他们对支持少数民族，妇女和本科生的研究有坚定的承诺（例如，通过NSF REUS，包括通过该项目，ASU的NSF S-STEM计划；这种组合和活跃物质系统结合的任何突破都将需要采用随机系统，冷凝物理物理学，群体系统，机器人技术和分布式算法的分析和技术来理解和实现所需的群体动态，因此，将汇集不同的研究人员和教育不同的学科和专业研究者。新的研究方法和发现将被纳入多个研究生课程中，研讨会将为桥接多个学科提供教程，使年轻研究人员可以访问材料并有助于广泛传播结果。调查结果（包括开源代码）将在各个学科中发布，并将在我们的网页和ARXIV上提供。该项目通过将合奏视为由微观级别的可编程元素组成的积极物质，从物理学的角度探讨了群体机器人技术的基本面。该项目将遵循（宏 - ）以任务为导向的方法，并设计一个分布式随机算法框架，以设计和评估微观级别的算法，该算法将产生目标的新兴宏观行为。它解决的紧急行为包括压缩（在最小化周长的同时保持连通的社区的连贯性），桥接（以最有效的方式连接两个或更多位置），对准（确定方向的商定指导方向），抑制了障碍（集体流动性的动作），以及局部移动（集体移动）。其中许多都有有趣的匡威问题，这些问题也同样值得，例如探索（维持连接的人群，但要探索最大面积）和不结盟（代表无序的集合）。在某些情况下，集体行为的作用就像是液体系统在液体（无序）和固体（有序）状态之间发生变化的，如系统中的相变确定。该项目将探索随机和分布式算法，以严格实现这些目标。

项目成果

期刊论文数量（7）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

A Stochastic Approach to Shortcut Bridging in Programmable Matter

可编程物质中捷径桥接的随机方法

DOI：
10.1007/978-3-319-66799-7_9
发表时间：
2017
期刊：
DNA23
影响因子：
0
作者：
Andres Arroyo, Marta;Cannon, Sarah;Daymude, Joshua J;Randall, Dana;Richa, Andrea W
通讯作者：
Richa, Andrea W

Sampling biased monotonic surfaces using exponential metrics

使用指数度量对有偏差的单调曲面进行采样