Authors
Jiwu Wang, Huazhe Dou, Shunkai Zheng, Masanori Sugisaka
Corresponding Author
Jiwu Wang
Available Online 1 September 2015.
DOI
https://doi.org/10.2991/jrnal.2015.2.2.7
Keywords
Arm robot, Target recognition, Flexible control, Machine vision
Abstract
In order to improve the applications for an industrial sorting robot, it
is necessary to increase its flexibility and control accuracy. Here an
industrial robot arm is designed and set up for experiment simulation with
machine vision. Some target recognition experiments are designed for vision
recognition. The flying badminton tracking experiment is given to verify
the efficiency of the developed algorithm. Moreover, the multiple target
recognition are also tested with our developed algorithms. The machine
vision technology is an effective solution. In order to reduce the influence
of the size, deformation, and lighting etc., the target recognition and
location method with fusion of scale invariant feature transform (SIFT)
and moment invariants is developed. The experiments results showed that
the developed image processing algorithms are robust, and the flexibility
of the industrial robot can be improved by machine vision.
Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).