Hostname: page-component-586b7cd67f-rdxmf Total loading time: 0 Render date: 2024-11-22T08:36:00.531Z Has data issue: false hasContentIssue false

Calibration-based absolute localization of parts for multi-robot assembly

Published online by Cambridge University Press:  24 June 2002

Edward J. Park
Affiliation:
Laboratory for Nonlinear Systems Control, Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario (Canada) M5S 3G8
Weihua Xu
Affiliation:
Laboratory for Nonlinear Systems Control, Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario (Canada) M5S 3G8
James K. Mills
Affiliation:
Laboratory for Nonlinear Systems Control, Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, Ontario (Canada) M5S 3G8

Abstract

In multi-robot assembly of parts, for successful mating, the grasped parts must be located with sufficiently small position and orientation errors so that assembly can be achieved. This paper describes a new approach for determining the absolute three-dimensional spatial location of parts grasped by robots during assembly. Through a combination of robot pose calibration and part-sensor calibration, the robot, used to grasp the part, is calibrated to accurately position and orient parts to a designated mating location. First, by employing a robot pose measurement system, the 6 DOF robot pose errors relative to a reference coordinate frame are compensated. Second, with the implementation of a part pose measurement, the 6 DOF part pose errors, relative to the robot tool frame, are estimated in real time. An experimental verification of the proposed methodology using a single FANUC S–110 robot manipulating an automotive sheet metal part is described.

Type
Research Article
Copyright
© 2002 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)