Intelligent, Real-Time Complex Computing Systems

智能、实时复杂计算系统

基本信息

批准号：
9208920
负责人：
W Richards Adrion
金额：
$ 113万
依托单位：
University of Massachusetts Amherst
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
1992
资助国家：
美国
起止时间：
1992-09-01 至 1996-02-29
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=9208920&HistoricalAwards=false
关键词：
Intelligent Real Time Complex Computing

项目摘要

This is the first year of a three year continuing award. The effort focuses on coordinated research in robotics, vision, real- time AI, and real-time software systems, in the context of a robotic assembly testbed. The emphasis is on flexible manufacturing automation involving active perception, planning, and cooperative activities among agents in real time. The project investigates integration of dextrous manipulation and vision, with cooperation among static and mobile robots and humans, and addresses current limitations of robotic systems in dealing with uncertainties and rapidly changing environments and tasks (such as occur in short-run production). Activities include development of multiple resolution representations which permit arbitration between local reflexive and global combinatoric strategies; studying tradeoffs between solution quality and computational speed in real-time systems; modeling cooperation and communication to achieve goal-oriented behavior; integrating architectures and algorithms for extracting relevant environmental information for control of distributed robotic manipulators; implementation of active perception to support model-based, goal oriented sensing for manufacturing assembly operations; constructing high level symbolic approaches to reasoning about geometry; and implementing learning mechanisms which model the environment based on experience over a general class of tasks to guide perception, planning, and multi-agent cooperation.

这是连续三年颁发奖项的第一年。这项工作的重点是在机器人装配测试台的背景下，对机器人技术、视觉、实时人工智能和实时软件系统进行协调研究。重点是灵活的制造自动化，涉及代理之间的实时主动感知、规划和合作活动。该项目研究了灵巧操作和视觉的集成，以及静态和移动机器人与人类之间的合作，并解决了机器人系统当前在处理不确定性和快速变化的环境和任务（例如在短期生产中发生）方面的局限性。活动包括开发多种解决方案表示，允许在局部自反策略和全局组合策略之间进行仲裁；研究实时系统中解决方案质量和计算速度之间的权衡；建模合作和沟通以实现目标导向的行为；集成用于提取相关环境信息以控制分布式机器人操纵器的架构和算法；实施主动感知，以支持制造装配操作中基于模型、面向目标的传感；构建高级符号方法来推理几何；实施学习机制，根据一般任务类别的经验对环境进行建模，以指导感知、规划和多智能体合作。