CAREER: Resource-adaptive distributed estimation for teams of micro aerial vehicles

职业：微型飞行器团队的资源自适应分布式估计

• 批准号: 1253314
• 负责人: Anastasios Mourikis
• 金额: $ 48.72万
• 依托单位: University of California-Riverside
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2020-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1253314&HistoricalAwards=false
• 关键词: CAREER; Resource; adaptive; distributed; estimation

The proposed work focuses on developing resource-adaptive distributed estimation algorithms for teams of micro aerial vehicles (MAVs). Among the several challenges one faces when designing estimators for MAV teams, the most important one is the stringent resource limitations of MAVs. While in any engineered system the resources are inevitably finite, cost, power, and weight considerations make the limitations particularly strict for teams of small MAVs. In this work, we will develop a rigorous, optimization-based framework for the design of estimation and inference algorithms, as well as for the design of the MAV platforms themselves. Our approach will yield distributed estimators capable of optimally allocating the sensing, processing, communication, and energy resources of an MAV team. The methods to be developed will lead to efficient design tools, and will permit a systematic study of the tradeoff curves between MAV resource availability and estimation performance.The algorithms and theoretical results that will result from this effort will dramatically increase the capabilities of MAV teams, in domains ranging from scientific exploration to search-and-rescue operations. In turn, these systems will yield benefits that will directly impact our lives, from advancing our state of scientific understanding to saving humans in disaster sites. Additionally, the proposed research plan will create opportunities for both graduate and undergraduate students from UC Riverside's diverse student body to conduct meaningful research. Undergraduate students will be recruited to work on new MAV designs, and it is anticipated that such an involvement will increase the likelihood of them pursuing a graduate education. Moreover, as part of an integrated outreach program, we will leverage the nature of the proposed research (flying robots capture the imagination of young minds) to inspire and recruit underrepresented minority students to science and engineering. These efforts will aid in closing the educational attainment gap for underrepresented groups.

建议的工作重点是开发资源自适应分布式估计算法的微型飞行器（MAVs）的团队。在为MAV团队设计估算器时面临的几个挑战中，最重要的一个是MAV严格的资源限制。虽然在任何工程系统中，资源都不可避免地是有限的，但成本、功率和重量的考虑使得小型MAV团队的限制特别严格。在这项工作中，我们将开发一个严格的，基于优化的框架，用于设计的估计和推理算法，以及设计的MAV平台本身。我们的方法将产生分布式估计能够最佳分配的传感，处理，通信和能源资源的MAV团队。这些方法的发展将导致有效的设计工具，并将允许MAV的资源可用性和估计性能之间的权衡曲线的系统研究，算法和理论结果，将导致从这一努力将显着提高MAV团队的能力，在从科学探索到搜索和救援行动的领域。反过来，这些系统将产生直接影响我们生活的好处，从推进我们的科学理解到拯救灾难现场的人类。此外，拟议的研究计划将创造机会，为研究生和本科生从加州大学滨江的多样化的学生团体进行有意义的研究。将招募本科生从事新的MAV设计工作，预计这种参与将增加他们攻读研究生教育的可能性。此外，作为综合推广计划的一部分，我们将利用拟议研究的性质（飞行机器人捕捉年轻人的想象力）来激励和招募代表性不足的少数民族学生从事科学和工程。这些努力将有助于缩小代表性不足群体的教育程度差距。