Intelligent, Real-Time Complex Computing Systems

这是连续三年获奖的第一年。 的 努力的重点是机器人、视觉、真实的 时间人工智能和实时软件系统，在一个 机器人装配试验台 重点在于灵活性 制造自动化涉及主动感知、规划 以及真实的代理之间的协作活动。 的 该项目研究了将神经元操纵和 视觉，静态和移动的机器人之间的合作， 人类，并解决了目前的机器人系统的限制， 应对不确定性和快速变化的环境， 任务（例如在短期生产中发生的任务）。 活动 包括开发多分辨率表示法， 允许局部自反和全局之间的仲裁 组合策略;研究解决方案之间的权衡 实时系统的质量和计算速度.建模 合作与沟通，实现目标导向的行为; 集成架构和算法， 用于分布式机器人控制的环境信息 机械手;主动感知的实现，以支持 用于制造装配的基于模型的、面向目标的感测 操作;构建高级符号方法， 几何推理;以及实施学习机制 它根据经验对环境进行建模， 引导感知、规划和多智能体的任务类别 合作

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.