Intelligent Material Handling Systems: Behavior-Based Control for Autonomous Tending of Manufacturing Workcells

智能物料搬运系统：基于行为的制造工作单元自主管理控制

• 批准号: 9113802
• 负责人: Max Donath
• 金额: $ 30万
• 依托单位: University of Minnesota-Twin Cities
• 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: 1992-02-15 至 1995-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9113802&HistoricalAwards=false
• 关键词: Intelligent; Material; Handling; Systems; Behavior

This material handling project addresses behavior based control for autonomous tending of manufacturing workcells. Automation systems assume that all objects are where they are supposed to be and that sensors and machines function as they are meant to. Failure to satisfy these assumptions can often result in catastrophic failure. Methodologies that facilitate the integration of sensors, computers and machines in order to autonomously accomplish complex tasks, i.e. sensing and dealing with the unexpected, are not well developed at all. This project proposes a behavioral control strategy to accomplish these tasks. The idea is based on observations of naturally occurring examples of autonomous systems, such as animal behavior. The strategy is based on the implementation of multiple behaviors taking advantage of multiple sensors and actuators functioning concurrently. Such ideas have been tested on robots, and the result has been to provide a successful strategy for robust operation in dynamically changing, unstructured environments. This project proposes to use this approach in the tending of machine tools used for low volume batch manufacturing, including the transfer of tool and parts among stations on the shop floor. With the experience gained in this research, progress is expected towards the long term goal of developing a general methodology for designing and building an hierarchical structure of integrated behaviors which can be use to address many generic material handling issues.***//

这个材料处理项目地址基于行为的控制 用于自主管理制造工作单元。 自动化 系统假定所有的物体都在它们应该在的地方 以及传感器和机器的功能。 不满足这些假设往往会导致 灾难性的失败 有助于实现可持续发展目标的方法 传感器、计算机和机器的集成， 自主完成复杂的任务，即感知和处理 与意想不到的，没有得到很好的发展。 这个项目 提出了一种行为控制策略来完成这些任务。 这个想法是基于对自然发生的例子的观察 自主系统的研究，比如动物行为。 该战略是 基于多行为采集的实现， 多个传感器和执行器的优势 同时。 这些想法已经在机器人上进行了测试， 结果是提供了一个成功的战略， 在动态变化的非结构化环境中运行。 本项目拟采用这种方法， 用于小批量生产的机床，包括 在车间各工位之间转移工具和零件。 根据这项研究所取得的经验， 制定一个通用方法的长期目标 设计和建立一个层次结构， 集成行为，可用于解决许多通用 材料处理问题。*//