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The Canonical Robot Command Language (CRCL)

Published

Author(s)

Frederick M. Proctor, Stephen B. Balakirsky, Zeid Kootbally, Thomas R. Kramer, Craig I. Schlenoff, William P. Shackleford

Abstract

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 offline 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. Using CRCL, a manufacturer can quickly develop robotic applications that meet customer demands for short turnaround, enable portability across a range of vendor equipment, and maintain investments in application development through reuse.
Citation
Industrial Robot-An International Journal
Volume
43
Issue
5

Citation

Proctor, F. , Balakirsky, S. , Kootbally, Z. , Kramer, T. , Schlenoff, C. and Shackleford, W. (2016), The Canonical Robot Command Language (CRCL), Industrial Robot-An International Journal, [online], https://doi.org/10.1108/IR-01-2016-0037 (Accessed March 29, 2024)
Created August 1, 2016, Updated December 3, 2018