CAREER: Probabilistic Methods for Multi-Robot Collaboration

职业：多机器人协作的概率方法

• 批准号: 0093406
• 负责人: Dieter Fox
• 金额: $ 44万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-03-15 至 2007-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0093406&HistoricalAwards=false
• 关键词: CAREER; Probabilistic; Methods; Multi; Robot

The project addresses development of systems that interact autonomously with their environment in an intelligent way. Applications range from intelligent home environments to autonomous mobile robots to software agents. Over the recent years, the use of probabilistic methods has led to development of reliable mobile robot systems. However, despite tremendous potential benefits of collaboration between robots, some fundamental issues in the context of probabilistic methods for multi-robot collaboration remain unexplored. The goal of this project is to bridge the scientific gap between probabilistic methods for single-robot systems and those for collaborative multi-robot systems. The research is expected to have a strong impact on the area of collaborating mobile robots. On the education side, in order to teach the skills needed to understand and develop such complex systems, a new undergraduate course on mobile robotics will be designed, which will follow a hands-on approach to teaching, involving students in investigative work with mobile robots.

该项目致力于开发以智能方式与环境自主交互的系统。应用范围从智能家庭环境到自主移动机器人再到软件代理。近年来，概率方法的应用导致了可靠移动机器人系统的发展。然而，尽管机器人之间的协作具有巨大的潜在好处，但在多机器人协作的概率方法背景下，一些基本问题仍未得到探索。该项目的目标是弥合单机器人系统的概率方法与协作多机器人系统的概率方法之间的科学差距。该研究预计将对协作移动机器人领域产生重大影响。在教育方面，为了教授理解和开发这种复杂系统所需的技能，将设计一门新的移动机器人本科课程，该课程将遵循动手教学的方法，让学生参与移动机器人的调查工作。