Jiwu Wang, Huazhe Dou, Shunkai Zheng, Masanori Sugisaka
Available Online 1 September 2015.
Arm robot, Target recognition, Flexible control, Machine vision
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.
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).