High-Level Local Control Strategies for the Coordination of Large Groups of Mobile Autonomous Agents

用于协调大型移动自治代理组的高级本地控制策略

• 批准号: 0322967
• 负责人: A. Morse
• 金额: $ 20万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0322967&HistoricalAwards=false
• 关键词: Level; Local; Control; Strategies; Coordination

Intellectual Merit: Remarkable advances have been made in recent years in the developmentof small, agile, relatively inexpensive mobile autonomous vehicles, ultimately intended for a widevariety of purposes such as search and rescue, exploration, environmental monitoring, distributedsensing, the cleaning and maintaining of structures, etc. The existence of such vehicles and theanticipated development of still more advanced versions raises compelling questions: Can largenumbers of small autonomous vehicles be successfully deployed in the form of a "swarm" or "flock"as a search team, an exploration group, or something similar, to cooperatively carry out a pre-scribedtask and to respond as a group to high-level management commands? Can such a groupreliably function robustly, in a difficult or even uninhabitable environment such as outer space orunder sea, possibly without a designated leader, with limited communications between its mem-bers,and/or with the "roles"of its members not all the same and perhaps changing with time?What can we learn about how to organize these groupings from biological groupings such as insectswarms, bird ocks, and fish schools? Is there a hierarchy of "compatible" models appropriate toswarming/schooling/ ocking which is rich enough to explain these behaviors at various "resolutions"ranging from aggregate characterizations of emergent behavior, to "point models" for eachvehicle, to even more detailed descriptions which model individual vehicle dynamics? In broadterms, these are the issues we propose to addressMore specifically, we propose to study distributed multi-vehicle motion control algorithms withthe aim of better understanding the concepts upon which large classes of such algorithms mightdepend. For example, we would like to better understand the implications of changing nearestneighbor sets and how this intrinsic property can be modelled and analyzed within the contextof switched dynamical systems. We would also like to understand how to analyze asynchronoussystems, which because of coarse modelling, exhibit non-deterministic state transitions. We alsopropose to explore, devise and evaluate alternative data structures/models at various degrees ofgranularity for representing large homogeneous/hetrogeneous groups of mobile autonomous agentsmoving in a densely populated environment. These representations are needed for a variety ofpurposes: for overall management of a large group, for simulating the effects of various protocolson group behavior, etc. Example data structures could include "rigid point formations" and"Euclidean Distance Matrices" as well as other graph-theoretic concepts and vehicle models andvarious levels of abstraction.Broader Impacts: This project will advance discovery and understanding while promoting teaching,training and learning in at least two different ways. First, graduate students involved inthe project will be expected to attend and present there results at technical meetings. Second,project graduate students will contribute to and participate in a short course on the topic whichwe envision organizing and giving towards the end of the project. We cannot think of any especiallyunusual way in which this project might broaden participation of underrepresented groups,although we certainly would encourage such participation. This project will enhance infrastructurefor research and education in at least two ways. First we expect to continue our crossdisciplinarycollaboration with our environmental biologist colleagues with whom we've already been workingfor several years. Second, we expect to continue to collaborate with our experimentalist colleagueswho have built an underwater multi-vehicle testbed { originally conceived by this PI } for tryingout various control algorithms. We hope to continue to contribute to broadening dissemination toenhance scientific and technological understanding by organizing and running boni fide interdisciplinarytechnical gatherings like the forthcoming Block Island Workshop on Cooperative Controlwhich we've co-organized and which will take place in June, 2003.

智能优势：近年来，小型、灵活、相对便宜的移动自动驾驶汽车的发展取得了显著进展，最终用于各种用途，如搜索和救援、勘探、环境监测、分布式传感、清洁和维护结构等。这些车辆的存在以及更先进版本的预期开发提出了一个引人注目的问题：大量小型自动驾驶车辆能否以“蜂群”或“羊群”的形式成功部署，作为搜索团队、探索团队或类似的团队，共同执行预定任务，并作为一个团队对高层管理命令做出反应？这样一个群体能否在一个困难的甚至不适合居住的环境中，如外层空间或海底，可能没有指定的领导人，成员之间的沟通有限，成员的“角色”不完全相同，甚至可能随着时间的推移而变化？关于如何从昆虫群、鸟群和鱼群等生物类群中组织这些类群，我们能学到什么？是否存在一种“兼容”模型的层次结构，这种模型足够丰富，可以在各种“分辨率”下解释这些行为，从紧急行为的总体特征，到每辆车的“点模型”，甚至更详细地描述单个车辆的动力学？从广义上讲，这些是我们建议解决的问题。更具体地说，我们建议研究分布式多车运动控制算法，以便更好地理解此类算法可能依赖的概念。例如，我们想更好地理解改变最近邻集的含义，以及如何在切换动力系统的背景下建模和分析这种内在性质。我们还想了解如何分析异步系统，由于粗糙的建模，表现出不确定的状态转换。我们还建议探索、设计和评估不同粒度的替代数据结构/模型，以表示在人口密集的环境中移动的大型同质/异质移动自治代理群体。这些表示用于各种目的：用于大型组的全面管理，用于模拟各种协议对组行为的影响等。示例数据结构可以包括“刚性点形成”和“欧几里得距离矩阵”，以及其他图论概念和车辆模型以及各种抽象级别。更广泛的影响：该项目将促进发现和理解，同时以至少两种不同的方式促进教学、培训和学习。首先，参与该项目的研究生将被要求参加技术会议并展示他们的成果。其次，项目研究生将贡献并参与一个关于该主题的短期课程，我们设想在项目结束时组织和提供该主题。尽管我们肯定会鼓励这样的参与，但我们想不出这个项目有什么特别不寻常的方式可以扩大代表性不足群体的参与。该项目将至少从两个方面加强研究和教育的基础设施。首先，我们希望继续与我们的环境生物学同事进行跨学科合作，我们已经与他们合作了好几年。其次，我们希望继续与我们的实验主义同事合作，他们已经建立了一个水下多车辆试验台（最初由该PI构思），用于试验各种控制算法。我们希望通过组织和举办真诚的跨学科技术聚会，如即将于2003年6月举行的我们共同组织的布洛克岛合作控制研讨会，继续为扩大传播作出贡献，以增进科学和技术的了解。