Automatic Grasping Region Extraction Using Shape Profile Based and Geometrical Features Approach

Saint Saint Pyone, Wut Yi Win, Aung Myat San

Abstract


Many applications of robotics include the grasping and manipulation of objects. Working in assembly robotic environments, the robot has to accurately not only locate the part but also to recognize it in readiness for grasping. In order to determine a grasping position, it is necessary to recognize the types of object, and detect portions which are suitable for grasp. According to get the important data clearly and correctly from the images, the detection and extraction methods are essential. This paper is mainly focused on the method of extracting the PCA and Shaped Profile with geometrical feature. Our proposed method is the combination of shapes based approach with the ratio and hole features. The proposed system has been tested successfully to a dataset of 336 images for seven types of common hand tools and achieved good accuracy and less computation complexity for 2D images by using a single camera. The overall recognition accuracy of PCA method with geometrical feature approach is 69.0476% on the same set of test images whereas overall accuracy of shape profile based method with geometrical feature approach is 97.9167%. Base on the experiment, this system is robust for the industrial robots for grasping tasks. This paper intends to implement machine vision system for industrial robotic grasping tasks. 


Keywords


accuracy; grasping region extraction; PCA features; Shaped profile feature; machine vision.

Full Text:

PDF

References


I. López-Juárez, R. Rios-Cabrera, M Peña-Cabrera Fast Object Recognition for Grasping Tasks using Industrial Robots Computación y Sistemas Vol. 16 No. 4, pp. 421 432 ISSN 1405-5546, 2012.

S. Chen, B. Mulgrew, and P. M. Grant, “A clustering technique for digital communications channel equalization Using radial basis function networks,” IEEE Trans. on Neural Networks, vol. 4, pp. 570-578, July 1993.

J. U. Duncombe, “Infrared navigation—Part I: An assessment of feasibility,” IEEE Trans. Electron Devices, vol. ED-11, pp. 34-39, Jan. 1959.

A. Bicchi and V. Kumar, “Robotic grasping and contact: A review,” in IEEE International Conference on Robotics & Automation (ICRA). Citeseer, 2000, pp. 348–353.

A. T. Miller, S. Knoop, H. I. Christensen, and P. K. Allen, “Automatic grasp planning using shape primitives,” in IEEE International Conference on Robotics & Automation (ICRA), vol. 2. IEEE, 2003, pp.1824–1829.

A. T. Miller and P. K. Allen, “Graspit! a versatile simulator for robotic grasping,” Robotics & Automation Magazine, IEEE, vol. 11, no. 4, pp.110–122, 2004.

R. Pelossof, A. Miller, P. Allen, and T. Jebara, “An svm learning approach to robotic grasping,” in IEEE International Conference on Robotics & Automation (ICRA), vol. 4. IEEE, 2004, pp. 3512–3518. C.

A. T. Miller, S. Knoop, P. K. Allen, and H. I. Christensen, “Automatic grasp planning using shape primitives,” in ICRA, 2003.

D. Bowers and R. Lumia, “Manipulation of unmodeled objects using intelligent grasping schemes,” IEEE Trans Fuzzy Sys, vol. 11, no. 3, 2003.

A. Saxena, J. Driemeyer, and A. Y. Ng, “Robotic grasping of novel objects using vision,” The International Journal of Robotics Research, vol. 27, no. 2, pp. 157–173, 2008.

Gonzalez, Woods, E. R. C. R. E. S. L.: Digital Image Processing Using MATLAB, Pearson Prentice Hall Pearson Education, Iric, New Jersey, USA, 2004.

Mark Richardson, Principal Component Analysis, May 2009.

N. Yamagishi, Sh. Oe and K. Terada, “A Method of Distance Measurement by Using Monocular Camera”, The 36th SICE Annual Conference, 1997.

Saint Saint Pyone, and Wut Yi Win, " Object Recognition for Grasping Tasks using Industrial Robots", 7th International Conference on Science and Engineering, Dec 2016.

Saint Saint Pyone, Wut Yi Win and Aung Myat San, " Vision Based Extraction of Grasping Region of Objects ", 246th The IIER International Conference on Recent Innovations in Engineering and Technology (ICRIET), Singapore, 2nd Aug 2017, pp-16-21.


Refbacks

  • There are currently no refbacks.


 
  
 

 

  


About ASRJETS | Privacy PolicyTerms & Conditions | Contact Us | DisclaimerFAQs 

ASRJETS is published by (GSSRR).