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Design analysis and optimization of 6-DOF telemanipulator based on performance indices

Published online by Cambridge University Press:  14 September 2018

Seungnam Yu ,
Soonwoong Hwang ,
Jongkwang Lee ,
Byungsuk Park  and
Hyojik Lee
Seungnam Yu*
Affiliation:
Korea Atomic Energy Research Institute, Yuseong-gu, Daejeon 34057, Korea
Soonwoong Hwang
Affiliation:
Hanyang University, Sangnok-gu, Ansan, Gyeonggi-do 15588, Korea
Jongkwang Lee
Affiliation:
Korea Atomic Energy Research Institute, Yuseong-gu, Daejeon 34057, Korea
Byungsuk Park
Affiliation:
Korea Atomic Energy Research Institute, Yuseong-gu, Daejeon 34057, Korea
Hyojik Lee
Affiliation:
Korea Atomic Energy Research Institute, Yuseong-gu, Daejeon 34057, Korea
*
*Corresponding author. E-mails: snyu@kaeri.re.kr, hswfile@gmail.com, leejk@kaeri.re.kr, nbspark@kaeri.re.kr, hyojik@kaeri.re.kr
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Summary

In contrast to general industrial robots, which are operated in normal environments and are easily accessible by human workers, telemanipulators are typically designed to perform specific and extreme tasks in hazardous areas. Teleoperation systems are difficult-to-equip fully intuitive or automated control systems because these are the kinds of manipulator systems used as substitutes to perform tasks that humans have to guide directly because they may require tough, sensitive, or sophisticated handling motions. Basically, these kinds of tasks are difficult to remotely perform through a slave manipulator operated by a human unless modification and optimization of the system are conducted. In this regard, the target system dealt within this study has similar disadvantages even though it has a high degree of freedom (DOF) arm structure. The performance of the current system was quantitatively evaluated to optimize the structure according to the considered main tasks. This work presents the various performance indices utilized and analyzes the current design of the considered telemanipulator system. An optimal design approach using the parameters associated with the frequent motions of the considered 6-DOF telemanipulator is then proposed based on the conducted analyses.

Keywords

TelemanipulatorPerformance indexCondition numberManipulability ellipsoidModified dynamic conditioning index
Type
Articles
Information
Robotica , Volume 36 , Issue 12 , December 2018 , pp. 1822 - 1835
Copyright
Copyright © Cambridge University Press 2018 

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References

1. Liu, X. J., Wang, J. and Pritschow, G.. “Performance atlases and optimum design of planar 5R symmetrical parallel mechanisms,” Mech. Mach. Theory 41, 119–144 (2006).Google Scholar
2. Rout, B. K. and Mittal, R. K., “Screening of factors influencing the performance of manipulator using combined array design of experiment approach,” Robot. Comput.-Integr. Manuf. 25, 651–666 (2009).Google Scholar
3. Singh, J. R. and Rastegar, J., “Optimal synthesis of robot manipulators based on global kinematic parameters,” Mech. Mach. Theory 30 (4), 569–580 (1995).Google Scholar
4. Niku, S. B., Introduction to Robotics: Analysis, Systems, Applications (Prentice Hall, New Jersey, USA, 2001).Google Scholar
5. Strang, G., Linear Algebra and its Application (Academic Press, New York, 1976).Google Scholar
6. Yoshikawa, T., “Manipulability of robotic mechanisms,” Int. J. Robot. Res. 3, 3–9 (1985).Google Scholar
7. Hwang, S. W., Kim, H. G., Choi, Y. S., Shin, K. S. and Han, C. S., “Design optimization method for 7 DOF robot manipulator using performance indices,” Int. J. Precis. Eng. Manuf. 18 (3), 293–299 (2017).Google Scholar
8. Holland, J. H., Adaptation in Natural and Artificial Systems (University of Michigan Press, Michigan, USA, 1975).Google Scholar
9. Cho, I. J., You, G. S., Choung, W. M., Lee, E. P., Hong, D. H., Lee, W. K., Ku, J. H., Moon, S. I., Kwon, K. C. and Lee, K. I., Development of Demonstration Facility Design Technology for Advanced Nuclear Fuel Cycle Process, Technical Report of Korea Atomic Energy Research Institute, No. KAERI/RR-3414/2012 (2012).Google Scholar
10. Ku, J. H., Moon, S. I., Cho, I. J., Choung, W. M., You, G. S. and Kim, H. D., “Development of pyroprocess integrated inactive demonstration facility,” Procedia Chem. 7, 779–784 (2012).Google Scholar
11. Lee, J. K., Lee, H. J., Park, B. S. and Kim, K., “Bridge-transported bilateral master-slave servo manipulator system for remote manipulation in spent nuclear fuel processing plant,” J. Field Robot. 29 (1), 138–160 (2012).Google Scholar
12. Park, B. S., Lee, J. K., Lee, H. J., Yu, S. N. and Kim, K. H., “Remote Modular Design for a Bridge Transported Dual Arm Servo-Manipulator Applied in Pyroprocessing Facility,” Proceedings of the IEEE 11th International Conference on Control, Automation and Systems (ICCAS) (2011) pp. 1708–1711.Google Scholar
13. Angeles, J. and Lopez-Cajun, C. S., “Kinematic isotropy and the conditioning index of serial robotic manipulators,” Int. J. Robot. Res. 11 (6), 560–571 (1992).Google Scholar
14. Merlet, J. P., “Jacobian, manipulability, condition number, and accuracy of parallel robots,” J. Mech. Des. 128 (1), 199–206 (2006).Google Scholar
15. Ma, O. and Angeles, J., “The Concept of Dynamic Isotropy and its Applications to Inverse Kinematics and Trajectory Planning,” Proceedings of the IEEE International Conference on Robotics and Automation, vol. 1 (1990) pp. 481–486.Google Scholar
16. Loduha, T. A. and Ravani, B., “On first-order decoupling of equations of motion for constrained dynamical systems,” Trans. ASME, 62, 216–222 (1995).Google Scholar