RI: Small: RUI: Fission-Fusion Multi-Robot Systems

RI：小型：RUI：裂变融合多机器人系统

• 批准号: 1617838
• 负责人: Brent Eskridge
• 金额: $ 19.26万
• 依托单位: Southern Nazarene University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1617838&HistoricalAwards=false
• 关键词: RI; Small; RUI; Fission; Fusion

The ability to use teams of robots in real-world tasks, such as exploration, reconnaissance and search and rescue, depends on their ability to effectively cooperate in complex and dynamic environments. Unfortunately, determining the most effective team size for a given task depends on a variety of factors, often requires information not readily available, and can be computationally impractical. Observations from nature show that some animal societies exhibit frequent splits (fission) and merges (fusion) of subgroups without the coordination overhead frequently found in multi-robot systems. The goal of this research project is to use these insights from fission-fusion societies in nature as inspiration to implement similar behavior in multi-robot systems.This project will investigate the motivations and mechanisms that contribute to the fission of a team of robots into smaller groups and the fusion of smaller groups into a larger group, into sizes appropriate to a given task. Potential biological and environmental factors that contribute to individual decisions that result in the fission and fusion of groups and that have artificial analogues relevant to multi-robot systems will be identified using agent-based simulations. An emphasis will be placed on factors that contribute to an adaptive task-specific preferred group size. Once identified, these factors will be implemented on physical robots to evaluate the performance of the decision-making system within the constraints of physical robots. The decision-making system used will be implemented using an adaptive fuzzy behavior hierarchy and a collective decision-making model developed using observations of natural systems.

在现实世界中使用机器人团队的能力，例如探索，侦察和搜索和救援，取决于他们在复杂而动态的环境中有效合作的能力。不幸的是，确定给定任务的最有效的团队规模取决于各种因素，通常需要信息不容易获得，并且在计算上可能是不切实际的。 来自自然的观察表明，某些动物社会表现出频繁的分裂（裂变）和亚组的合并（融合），而没有协调的架空在多机器人系统中经常发现。 该研究项目的目的是利用本质上的裂变融合社会的这些见解作为在多机器人系统中实施相似行为的灵感。该项目将调查有助于将机器人裂变为较小的动机和机制组和较小的组融合到一个较大的组中，大小适合给定任务。 将使用基于代理的模拟来确定有助于导致群体裂变并具有与多机器人系统相关的人为类似物的单个决策的潜在生物学和环境因素。 将重点放在导致适应性任务特异性首选小组规模的因素上。 一旦确定，这些因素将在物理机器人上实施，以评估物理机器人限制内决策系统的性能。 所使用的决策系统将使用自适应模糊行为层次结构和使用自然系统观察开发的集体决策模型实施。