REU: CAREER: Motion Strategy Algorithms for Geometry-Intensive Applications

REU：职业：几何密集型应用的运动策略算法

• 批准号: 9875304
• 负责人: Steven Lavalle
• 金额: $ 40万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-05-15 至 2002-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9875304&HistoricalAwards=false
• 关键词: REU; CAREER; Motion; Strategy; Algorithms

This award supports an integrated research and education program that is centered on computing motion strategies in geometry-intensive applications. A healthy synergy will be obtained by balancing efforts between both core issues and specialized applications. The core of this research program is rooted in robot motion planning, and it is built on a broader unified mathematical framework that incorporates concepts from optimal control theory, computational geometry, statistical decision theory, and dynamic game theory. This leads to the proposed investigation of three core algorithmic issues: 1) searching high-dimensional spaces that have algebraic and differential constraints, 2)responding to unpredictable changes and on-line information, and 3) solving sensor-based tasks and processing incomplete information. The focus is significantly broader than traditional path planning. The core research is guided by efforts in several applications, such as mobile robotics with active sensing, virtual prototyping-hazardous environments. These research efforts are incorporated into an education plan that: 1)builds an interdisciplinary group of graduate students who are carefully guided through the education and research process, ii) introduces undergraduates to research, particularly through mobile robotics and graphical simulation projects, iii) takes steps towards an interdisiplinary curriculum in geometric algorithms, and iv) helps those from disadvantaged backgrounds to realize their potential and excel in their careers.

该奖项支持一个综合的研究和教育计划，该计划以几何密集型应用中的计算运动策略为中心。 通过平衡核心问题和专门应用之间的努力，将实现健康的协同作用。 该研究计划的核心是植根于机器人运动规划，它是建立在一个更广泛的统一的数学框架，结合了最优控制理论，计算几何，统计决策理论和动态博弈论的概念。 这导致了三个核心算法问题的研究：1）搜索具有代数和微分约束的高维空间，2）响应不可预测的变化和在线信息，以及3）解决基于传感器的任务和处理不完整的信息。 其重点比传统的路径规划要广泛得多。 核心研究是由几个应用程序，如移动的机器人与主动传感，虚拟样机危险环境的努力指导。 这些研究工作被纳入一项教育计划，该计划：1）建立一个跨学科的研究生群体，他们在教育和研究过程中得到精心指导，ii）向本科生介绍研究，特别是通过移动的机器人和图形模拟项目，iii）采取措施，建立几何算法的跨学科课程，及iv）协助弱势社群发挥潜能，在事业上有所作为。