single-au.php

IJAT Vol.16 No.6 pp. 870-878
doi: 10.20965/ijat.2022.p0870
(2022)

Paper:

Generation of a Robot Program and Determination of an Optimal Workpiece Placement Considering the Manipulability of Industrial Robots

Kei Moriguchi*,†, Takuya Mizokami**, and Koichi Morishige*

*Department of Mechanical and Intelligent Systems Engineering, Graduate School of Informatics and Engineering,
The University of Electro-Communications
1-5-1 Chofugaoka, Chofu, Tokyo 182-8585, Japan

Corresponding author

**Faculty of Informatics and Engineering, Department of Mechanical and Intelligent Systems Engineering,
The University of Electro-Communications, Chofu, Japan

Received:
April 25, 2022
Accepted:
October 5, 2022
Published:
November 5, 2022
Keywords:
industrial robot, optimal workpiece placement, offline teaching, manipulability, welding operation
Abstract

Various operations in the production sites of manufacturing industries are being automated using industrial robots instead of operators. In recent years, an offline teaching method for robot motion has been implemented, where programs are generated in a work environment that is reproduced virtually inside a computer. However, the robot program developed using the offline teaching method can pass through singularities or suddenly change the robot’s posture, making the robot incapable of performing safe operations. To achieve optimal operation, the operator must determine the workpiece placement and create a robot program through trial and error. In this study, we proposed a method that uses manipulability to generate a program that commands the robot to move without passing singularities or changing the robot’s posture. Manipulability is quantitatively evaluated as an indicator of a robot’s ability to move its end effector in arbitrary directions. We proposed another method to determine the optimal workpiece placement for robot operations that can maximize the sum of manipulability during the operation. We implemented the aforementioned methods in an offline teaching system. We applied the developed system to a welding operation and verified its effectiveness by conducting motion simulations. The developed system was able to generate a practical robot program that maintained high manipulability and did not cause sudden changes in the posture or pass singularities. The developed system was able to simultaneously determine the optimal workpiece placement for the task, thereby confirming the usefulness of the proposed method.

Cite this article as:
K. Moriguchi, T. Mizokami, and K. Morishige, “Generation of a Robot Program and Determination of an Optimal Workpiece Placement Considering the Manipulability of Industrial Robots,” Int. J. Automation Technol., Vol.16 No.6, pp. 870-878, 2022.
Data files:
References
  1. [1] K. Morishige, Y. Ueki, T. Ishida, and Y. Takeuchi, “Automation of Polishing Process with Industrial Robots: Polishing Path Generation in Consideration of Surface Curvature (Multi-axis control machining and measurement),” Proc. of Int. Conf. on Leading Edge Manufacturing in 21st Century: LEM21, Vol.2005.1, pp. 109-114, 2005.
  2. [2] K. Okamoto and K. Morishige, “Polishing Process Automation by Industrial Robot with Polished Surface Quality Judgment Based on Image Processing – Visual Inspection Based on Pattern Matching,” Key Engineering Materials, Vols.523-524, pp. 481-486, 2012.
  3. [3] P. Neto, N. Mendes, R. Araújo, J. Norberto Pires, and A. Paulo Moreira, “High-level robot programming based on CAD: dealing with unpredictable environments,” Industrial Robot: An Int. J., Vol.39, No.3, pp. 294-303, 2012.
  4. [4] L. A. Ferreira, Y. L. Figueira, I. F. Iglesias, and M. Á. Souto, “Offline CAD-based Robot Programming and Welding Parametrization of a Flexible and Adaptive Robotic Cell Using Enriched CAD/CAM System for Shipbuilding,” Procedia Manufacturing, Vol.11, pp. 215-223, 2017.
  5. [5] S. Makita, T. Sasaki, and T. Urakawa, “Offline Direct Teaching for a Robotic Manipulator in the Computational Space,” Int. J. Automation Technol., Vol.15, No.2, pp. 197-205, 2021.
  6. [6] B. Nelson and M. Donath, “Optimizing the location of assembly tasks in a manipulator’s workspace,” J. of Robotic Systems, Vol.7, No.6, pp. 791-811, 1990.
  7. [7] M. B. Trabia and M. Kathari, “Placement of a manipulator for minimum cycle time,” J. of Robotic Systems, Vol.16, No.8, pp. 419-431, 1999.
  8. [8] K. Abdel-Malek and W. Yu, “Placement of Robot Manipulators to Maximize Dexterity,” Int. J. of Robotics and Automation, Vol.19, 2000.
  9. [9] N. Vahrenkamp, T. Asfour, and R. Dillmann, “Robot placement based on reachability inversion,” Proc. of the 2013 IEEE Int. Conf. on Robotics and Automation, pp. 1970-1975, 2013.
  10. [10] F. Zacharias, C. Borst, and G. Hirzinger, “Capturing robot workspace structure: representing robot capabilities,” Proc. of the 2007 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, pp. 3229-3236, 2007.
  11. [11] T. Yoshikawa, “Manipulability of Robotic Mechanisms,” The Int. J. of Robotics Research, Vol.4, No.2, pp. 3-9, 1985.
  12. [12] K. Morishige and Y. Sato, “Optimization of Workpiece Placement in Sealing Operation Using Industrial Robot Considering Manipulability,” Proc. of the Int. Symp. on Flexible Automation, Vol.2018, pp. 100-105, 2018.
  13. [13] A. D. M. Martins, A. M. Dias, and P. J. Alsina, “Comments on Manipulability Measure in Redundant Planar Manipulators,” Proc. of the 2006 IEEE 3rd Latin American Robotics Symp., pp. 169-173, 2006.
  14. [14] PQP – A Proximity Query Package. https://gamma.cs.unc.edu/SSV/ [Accessed March 22, 2022]
  15. [15] VERICUT. https://main.vericut.jp/ [Accessed March 22, 2022]
  16. [16] T. Yoshikawa, “Foundations of Robot Control,” Corona Publishing Co., Ltd., 1988 (in Japanese).

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 01, 2024