Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-28T15:12:23.661Z Has data issue: false hasContentIssue false

Simultaneous base and tool calibration for self-calibrated parallel robots

Published online by Cambridge University Press:  24 June 2002

Guilin Yang
Affiliation:
Automation Technology Division, Gintic Institute of Manufacturing Technology (Singapore), 638075.
I-Ming Chen
Affiliation:
School of Mechanical & Production Engineering, Nanyang Technological University (Singapore), 639798.
Song Huat Yeo
Affiliation:
School of Mechanical & Production Engineering, Nanyang Technological University (Singapore), 639798.
Wee Kiat Lim
Affiliation:
DSO National Laboratories (Singapore), 118230.

Abstract

In this paper, we focus on the base and tool calibration of a self-calibrated parallel robot. After the self-calibration of a parellel robot by using the built-in sensors in the passive joints, its kinematic transformation from the robot base to the mobile platform frame can be computed with sufficient accuracy. The base and tool calibration, hence, is to identify the kinematic errors in the fixed transformations from the world frame to the robot base frame and from the mobile platform frame to the tool (end-effector) frame in order to improve the absolute positioning accuracy of the robot. Using the mathematical tools from group theory and differential geometry, a simultaneous base and tool calibration model is formulated. Since the kinematic errors in a kinematic transformation can be represented by a twist, i.e. an element of se(3), the resultant calibration model is simple, explicit and geometrically meaningful. A least-square algorithm is employed to iteratively identify the error parameters. The simulation example shows that all the preset kinematic errors can be fully recovered within three to four iterations.

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.)