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RI: Medium Collaborative Research: Minimalist Mapping and Monitoring

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
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-08-01 至 2013-07-31

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中文摘要
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英文摘要
"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.
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NRI: Large: Collaborative Research: Human-robot Coordinated Manipulation and Transportation of Large Objects
CPS: Small: Sensor Lattices
Expanding the Frontiers of Motion Planning: Feedback, Differential Constraints, and Resolution Completeness
REU: CAREER: Motion Strategy Algorithms for Geometry-Intensive Applications
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