Proctor Frederick M, Balakirsky Stephen B, Kootbally Zeid, Kramer Thomas R, Schlenoff Craig I, Shackleford William P
National Institute of Standards and Technology.
Georgia Institute of Technology.
Ind Rob. 2016;43(5):495-502. doi: 10.1108/IR-01-2016-0037.
Industrial robots can perform motion with sub-millimeter repeatability when programmed using the teach-and-playback method. While effective, this method requires significant up-front time, tying up the robot and a person during the teaching phase. Off-line programming can be used to generate robot programs, but the accuracy of this method is poor unless supplemented with good calibration to remove systematic errors, feed-forward models to anticipate robot response to loads, and sensing to compensate for unmodeled errors. These increase the complexity and up-front cost of the system, but the payback in the reduction of recurring teach programming time can be worth the effort. This payback especially benefits small-batch, short-turnaround applications typical of small-to-medium enterprises, who need the agility afforded by off-line application development to be competitive against low-cost manual labor. To fully benefit from this agile application tasking model, a common representation of tasks should be used that is understood by all of the resources required for the job: robots, tooling, sensors, and people. This paper describes an information model, the Canonical Robot Command Language (CRCL), which provides a high-level description of robot tasks and associated control and status information.
当使用示教再现方法进行编程时,工业机器人能够以亚毫米级的重复性执行运动。虽然这种方法很有效,但它需要大量的前期时间,在示教阶段会占用机器人和操作人员的时间。离线编程可用于生成机器人程序,但除非辅以良好的校准以消除系统误差、采用前馈模型来预测机器人对负载的响应以及进行传感以补偿未建模的误差,否则这种方法的精度很差。这些措施会增加系统的复杂性和前期成本,但减少重复示教编程时间所带来的回报可能是值得付出努力的。这种回报对于中小企业典型的小批量、短周转应用尤其有益,这些企业需要离线应用开发所提供的灵活性来与低成本的体力劳动竞争。为了充分受益于这种灵活的应用任务模型,应该使用一种所有工作所需资源(机器人、工具、传感器和人员)都能理解的通用任务表示形式。本文描述了一种信息模型,即规范机器人命令语言(CRCL),它提供了对机器人任务以及相关控制和状态信息的高级描述。