SGER: Impact of Intermittent Networks on Team-based Coverage

SGER：间歇性网络对基于团队的覆盖范围的影响

• 批准号: 0846976
• 负责人: Monica Anderson
• 金额: --
• 依托单位: University of Alabama Tuscaloosa
• 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 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0846976&HistoricalAwards=false
• 关键词: SGER; Impact; Intermittent; Networks; Team

Situational awareness is increasingly reliant on unmanned vehicle teams to provide information by constant wide area surveillance. Issues of how to best coordinate the actions of many autonomous agents, individually or in teams, in order to accomplish the search goal of complete and timely coverage are essential for the robust information. Unfortunately, the application of robot teams in coverage tasks has many unaddressed facets of complexity. Specifically, the propagation constraints of networks limit the ability for robot teams to facilitate cooperation using digital networks. In this project, we investigate the cooperation problem with a focus on modeling and experimentation in the presence of real world network constraints. This research project aims to use bio-inspired cooperation paradigms to: 1) improve large-scale search and surveillance by actively predicting and managing network constraints based on role assignment, proximity-based sub-team formation, and communication through observation, 2) study of message age and impact upon performance, and 3) study of proximity to message importance. It is expected that results will be in line with previous work that shows that less communication can result in better cooperation in certain areas and team sizes.

态势感知越来越依赖于无人驾驶车辆团队通过持续的广域监视提供信息。 如何最好地协调许多自主代理人的行动，单独或在团队中，以完成搜索目标的完整和及时的覆盖问题是必不可少的强大的信息。不幸的是，机器人团队在覆盖任务中的应用有许多未解决的复杂性方面。 具体而言，网络的传播约束限制了机器人团队使用数字网络促进合作的能力。 在这个项目中，我们调查的合作问题，重点是建模和实验中存在的真实的世界网络的约束。本研究项目旨在使用生物启发的合作范式：1）通过基于角色分配，基于邻近度的子团队形成和通过观察进行通信的积极预测和管理网络约束来改善大规模搜索和监视，2）研究消息年龄和对性能的影响，以及3）研究消息重要性的邻近度。 预计结果将与以前的工作一致，表明减少沟通可以在某些领域和团队规模上实现更好的合作。