By Topic

Hand-eye calibration of measurement robot based on multi-population particle swarm optimization

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Aiguo Li ; Dalian Maritime Univ, Dalian ; Zi Ma ; Ying Hu ; Na Lin

A robot can be used to non-contact measurement with a structured-light scanner fixed to its end effector. In order to transform the 2-dimension values measured by the sensor into the 3-dimension values in the world frame, the geometric model of the system is established. A method to estimate hand-eye matrix is presented, which uses a radius-known ball, whose center is derived from the least square fitting method to enable the sensor to measure a fixed point (ball center) from different views. Thus hand-eye calibration is converted to unconstraint optimization problem. A multi-population particle swarm optimization (MPSO) is used to search hand-eye matrix, which merges the advantages of the global PSO and local PSO. Simulation and experiment show the ability of the algorithm.

Published in:

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Date of Conference:

25-27 June 2008