By Topic

Virtual-reality-based point-and-direct robotic inspection in manufacturing

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
$33 $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

2 Author(s)
C. Wang ; Graduate Sch. of Ind. Eng. & Manage., Chung Hua Polytech. Inst., Hsin Chu, Taiwan ; D. J. Cannon

This paper explores a flexible manufacturing paradigm in which robot grasping is interactively specified and skeletal images are efficiently used in combination to allow rapidly setting up surface flaw identification tasks in small-quantity/large-variety manufacturing. Two complementary technologies are combined to make implementation of inspection as rapid as possible. First, a novel material handling approach is described for robotic picking and placing of parts onto an inspection table using virtual tools. This allows an operator to point and give directives to set up robotic inspection tasks. Second, since specification may be approximate using this method, a fast and flexible means of identifying images of perfect and flawed parts is explored that avoids rotational or translational restrictions on workpiece placement. This is accomplished by using skeleton pixel counts as neural network inputs. The total system, including material handling and skeleton-based inspection, features flexibility during manufacturing set-up, and reduces the process time and memory requirements for workpiece inspection

Published in:

IEEE Transactions on Robotics and Automation  (Volume:12 ,  Issue: 4 )