RI: Adaptive Motion Coordination of Multiple Unmanned Aerial Vehicles for the Monitoring of Aerosol-Dust-Cloud-Radiation Interactions

RI：多架无人机的自适应运动协调，用于监测气溶胶-尘埃-云-辐射相互作用

• 批准号: 0712746
• 负责人: Sonia Martinez
• 金额: $ 27.07万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0712746&HistoricalAwards=false
• 关键词: RI; Adaptive; Motion; Coordination; Multiple

The main objective of this project is the development of scalable,systematic approaches to the synthesis of adaptive sampling strategiesby mobile sensor networks. In particular, the research challenges havebeen identified with a specific application in mind: the study ofatmospheric aerosol-dust-cloud-radiation interactions, and howaerosols and dust affect cloud microphysics and, more generally,climate dynamics. The successful completion of the project requiresprogress on the development of distributed data fusion algorithms thathelp estimate spatio-temporal processes and coordination algorithmsthat exploit these environmental filters. The resulting motion planswill be adapted for the sampling of aerosols and dust on clouds acrossareas of the Pacific Ocean.The novel conceptual tools developed in the framework of this projectwill allow the further development of mobile robotic networks withcapabilities that are well beyond those offered by the currenttechnology. Algorithms and motion plans will be adapted and tested ina multi-UAV system specially developed to monitor atmosphericprocesses. The possibility of having a network of mobile roboticvehicles collecting in-situ data in real time will greatly extend ourabilities for remote measurement and actuation. In particular, thedynamic adaptive gathering of atmospheric data by groups of UAVs willprovide a much needed insight into how human activity affects climatechange.

这个项目的主要目标是发展可扩展的，系统的方法来合成的自适应采样strategiesby移动的传感器网络。特别是，研究挑战已经确定了一个具体的应用：研究大气气溶胶-灰尘-云-辐射的相互作用，以及气溶胶和灰尘如何影响云的微物理学，更普遍的是，气候动力学。 该项目的成功完成需要分布式数据融合算法的发展，帮助估计时空过程和协调算法，利用这些环境过滤器的进展。 由此产生的运动计划将适用于横跨太平洋区域的云上气溶胶和尘埃的采样。在该项目框架内开发的新概念工具允许进一步开发移动的机器人网络，其能力远远超出当前技术所提供的能力。算法和运动计划将在专门开发的多无人机系统中进行调整和测试，以监测大气过程。 有一个移动的机器人车辆网络收集现场数据在真实的时间的可能性将大大扩展的分辨率为远程测量和驱动。特别是，无人机组对大气数据的动态自适应收集将为人类活动如何影响气候变化提供急需的洞察力。