RI: Medium Collaborative Research: Minimalist Mapping and Monitoring

RI：中等协作研究：极简制图和监测

• 批准号: 0905523
• 负责人: Steven Lavalle
• 金额: $ 43.2万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-08-01 至 2013-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0905523&HistoricalAwards=false
• 关键词: RI; Medium; Collaborative; Research; Minimalist

"This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5)."This project addresses fundamental and challenging questions that are common to robotic systems that build their own maps and solve monitoring tasks. In particular, the work contributes to our general understanding of the interplay between sensing, control, and computation as people attempt to design systems that minimize costs and maximize robustness.Powerful new abstractions, planning algorithms, and control laws that accomplish basic mapping and monitoring operations are being developed in this effort. This is expected to lead to improved technologies in numerous settings where mapping and monotoring are basic components.Ample motivation is provided by technological challenges that involve searching, tracking, and monitoring the behavior of people, wildlife, and robots. Examples include search-and-rescue, security sweeps, mapping abandoned mines, scientific study of endangered species, assisted living, ground-based military operations, and even analysis of shopping habits. The work is particularly transformative because it lives outside of the traditional boundaries of algorithms, computational geometry, sensor networks, control theory, and robotics. Furthermore, national interest continues to grow in the direction of developing distributed robotic systems that combine sensing, actuation, and computation. By helping to break down traditional academic and scientific barriers, it is expected that the work will transform the way we think about robotics algorithms, the engineering design process, and the education of students across the robotics, computational geometry, and control disciplines.

“这项奖励是根据2009年美国复苏和再投资法案（公法111-5）资助的。”该项目解决了机器人系统构建自己的地图和解决监控任务时常见的基本和具有挑战性的问题。特别是，当人们试图设计成本最小化和鲁棒性最大化的系统时，这项工作有助于我们对传感、控制和计算之间相互作用的一般理解。强大的新抽象、计划算法，以及完成基本映射和监视操作的控制法则，正在这项工作中被开发出来。预计这将导致在绘图和监测是基本组成部分的许多环境中改进技术。包括搜索、跟踪和监控人类、野生动物和机器人行为在内的技术挑战提供了充足的动力。这方面的例子包括搜索和救援、安全清扫、绘制废弃矿井地图、濒危物种的科学研究、辅助生活、地面军事行动，甚至是购物习惯分析。这项工作尤其具有变革性，因为它超越了算法、计算几何、传感器网络、控制理论和机器人技术的传统界限。此外，国家利益继续向开发集传感、驱动和计算于一体的分布式机器人系统的方向发展。通过帮助打破传统的学术和科学障碍，预计这项工作将改变我们对机器人算法、工程设计过程以及机器人、计算几何和控制学科的学生教育的看法。