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.

该项目解决了以智能方式与环境自动互动的系统的开发。应用程序范围从智能家庭环境到自动移动机器人到软件代理。 近年来，概率方法的使用导致了可靠的移动机器人系统的发展。但是，尽管机器人之间的协作巨大潜在的好处，但在概率方法中，一些基本问题仍未得到探索。该项目的目的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。 预计该研究将对合作移动机器人的领域产生强大的影响。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，将设计一个新的移动机器人本科课程，该课程将遵循动手的教学方法，使学生与移动机器人进行调查工作。