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Optimal torso design selection for dual 7-DOF robot arm using von Mises stress and workspace analysis

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Abstract

This paper presents a unique optimal torso design selection technique for the dual seven-degree-of-freedom robot arm. This optimal design enhances the robot end-effector’s workspace with less operational stress. The selection procedure incorporates the von Mises stress and robot workspace analysis in different robot-torso mounting configurations. The torso design selection strategy includes the von Mises stress calculation numerically and by using SolidWorks static analysis for robot arm considered as bolted-fixed end cantilever beam. Followed by robot end-effector workspace analysis using inverse kinematics, which determines the maximum area covered by manipulated robot end-effector in 2-dimensional (2D) and 3-dimensional (3D) space. Subsequently, introducing a selection function for torso design. This selection function is calculated based on weighting coefficients (priority given to stress and workspace), von Mises stress, and workspace area. The selection technique concludes that the torso design with upper-arm mounting configuration is optimal for current robot application, i.e., assembly.

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Acknowledgments

This research was funded by the Technology Innovation Program (10073147, Development of Robot Manipulation Technology by Using Artificial Intelligence) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea).

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Authors and Affiliations

  1. School of Mechanical Engineering, Pusan National University, Busan, 46241, Korea

    Hamza Khan, Saad Jamshed Abbasi & Min Cheol Lee

Authors
  1. Hamza Khan
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  2. Saad Jamshed Abbasi
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  3. Min Cheol Lee
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Corresponding author

Correspondence to Min Cheol Lee.

Additional information

Hamza Khan received the B.S. in Mechatronics Engineering from Air University, Islamabad, Pakistan, in 2018, and the M.S. in Mechanical Engineering from Pusan National University, Busan, South Korea, in 2021, where he is currently pursuing the Ph.D. degree in Mechanical Engineering. His research interests include linear/nonlinear control, force control, robot manipulators kinematics and dynamics and system identification.

Saad Jamshed Abbasi received the B.S. in Mechatronics Engineering from Air University, Islamabad, Pakistan, in 2015, and the M.S. in Mechanical Engineering from Pusan National University, Busan, South Korea, in 2018, where he is currently pursuing the Ph.D. in Mechanical Engineering. His research interests include nonlinear control, robot manipulators, and system identification.

Min Cheol Lee received the Ph.D. in Applied Physics and M.S. in Engineering Science from the University of Tsukuba, Tsukuba, Japan, in 1991 and 1988, respectively. He received his B.S. in Mechanical Engineering from Pusan National University, Busan, Korea in 1983. He is a Full Professor of Mechanical Engineering, Pusan National University, South Korea. His research interests include intelligent robot control, autonomous mobile robot, medical robot, signal processing to identify a system, robust control of a system, sensor application, and mechatronics.

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Khan, H., Abbasi, S.J. & Lee, M.C. Optimal torso design selection for dual 7-DOF robot arm using von Mises stress and workspace analysis. J Mech Sci Technol 35, 4149–4159 (2021). https://doi.org/10.1007/s12206-021-0827-2

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  • DOI: https://doi.org/10.1007/s12206-021-0827-2

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