During the manufacture of robotic systems differences between actual and nominal link lengths and orientations occur. In addition, errors between nominal and actual pair variables result from sensor and controller errors. Thus, when a robotic system attempts to perform a desired task using nominal motion planning schemes and nominal linkage kinematics, it will perform an actual task that is usually quite different from that desired. A procedure for determining the differences between the nominal and actual linkages parameters, pair variables, and tasks is presented. The approach can be used on all modern-day robots, as it incorporates solution techniques for the nonsquare and singular matrices that typically occur. An example using a PUMA 560 is included.
Skip Nav Destination
Article navigation
June 1986
This article was originally published in
Journal of Mechanisms, Transmissions, and Automation in Design
Research Papers
Determination of Linkage Parameter and Pair Variable Errors in Open Chain Kinematic Linkages Using a Minimal Set of Pose Measurement Data
R. Ibarra,
R. Ibarra
Department of Mechanical Engineering, University of Texas at Austin, Austin, TX
Search for other works by this author on:
N. D. Perreira
N. D. Perreira
Department of Mechanical Engineering and Mechanics and the Manufacturing Systems Engineering Program, Lehigh University, Bethlehem, PA 18015
Search for other works by this author on:
R. Ibarra
Department of Mechanical Engineering, University of Texas at Austin, Austin, TX
N. D. Perreira
Department of Mechanical Engineering and Mechanics and the Manufacturing Systems Engineering Program, Lehigh University, Bethlehem, PA 18015
J. Mech., Trans., and Automation. Jun 1986, 108(2): 159-166 (8 pages)
Published Online: June 1, 1986
Article history
Received:
June 11, 1985
Online:
November 19, 2009
Citation
Ibarra, R., and Perreira, N. D. (June 1, 1986). "Determination of Linkage Parameter and Pair Variable Errors in Open Chain Kinematic Linkages Using a Minimal Set of Pose Measurement Data." ASME. J. Mech., Trans., and Automation. June 1986; 108(2): 159–166. https://doi.org/10.1115/1.3260797
Download citation file:
Get Email Alerts
Cited By
DeepJEB: 3D Deep Learning-Based Synthetic Jet Engine Bracket Dataset
J. Mech. Des (April 2025)
Design and Justice: A Scoping Review in Engineering Design
J. Mech. Des (May 2025)
Related Articles
A Self-Calibration Method for Robotic Measurement System
J. Manuf. Sci. Eng (February,2000)
Motion Generation of Planar Six- and Eight-Bar Slider Mechanisms as Constrained Robotic Systems
J. Mechanisms Robotics (August,2015)
Motion Planning for Nonprehensile Object Manipulation Using Novel 5-Bar Linkage
J. Mechanisms Robotics (April,2025)
Instantaneous Kinematics of Parallel-Chain Robotic Mechanisms
J. Mech. Des (September,1992)
Related Proceedings Papers
Related Chapters
Time-Varying Coefficient Aided MM Scheme
Robot Manipulator Redundancy Resolution
Feedback-Aided Minimum Joint Motion
Robot Manipulator Redundancy Resolution
QP Based Encoder Feedback Control
Robot Manipulator Redundancy Resolution