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Research Papers

Analysis of Optimal Balancing for Robotic Manipulators in Repetitive Motions

[+] Author and Article Information
Amin Nikoobin

Robotics and Control Lab,
Faculty of Mechanical Engineering,
Semnan University,
Semnan 3513119111, Iran
e-mail: anikoobin@semnan.ac.ir

Mojtaba Moradi

Faculty of Computer and Electrical Engineering,
Semnan University,
Semnan 3513119111, Iran
e-mail: moradi.moj@gmail.com

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT,AND CONTROL. Manuscript received January 18, 2017; final manuscript received December 13, 2017; published online March 7, 2018. Assoc. Editor: Yunjun Xu.

J. Dyn. Sys., Meas., Control 140(8), 081002 (Mar 07, 2018) (8 pages) Paper No: DS-17-1034; doi: 10.1115/1.4039155 History: Received January 18, 2017; Revised December 13, 2017

Balancing plays a major role in performance improvement of robotic manipulators. From an optimization point of view, some balancing parameters can be modified to decrease motion cost. Recently introduced, this concept is called optimal balancing: an umbrella term for static balancing and other balancing methods. In this method, the best combination of balancing and trajectory planning is sought. In this note, repetitive full cycle motion of robot manipulators including different subtasks is considered. The basic idea arises from the fact that, upon changing dynamic equations of a robotic manipulator or cost functions in subtasks, the entire cycle of motion must be reconsidered in an optimal balancing problem. The possibility of cost reduction for a closed contour in potential fields is shown by some simulations done for a PUMA-like robot. Also, the obtained results show 34.8% cost reduction compared to that of static balancing.

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Figures

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Fig. 1

A general repetitive task with its subtasks and OCP parameters

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Fig. 2

Material handling (left) and arc gluing (right)

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Fig. 3

Heaviside-like functions defined for abstraction of tasks

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Fig. 8

Comparison of cost values for the normal, static, and optimal cases

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Fig. 7

Applied torques onto the joints for the (a) normal, (b) static, and (c) optimal cases

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Fig. 4

A schematic of the considered PUMA-like robot

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Fig. 6

Angular velocity of the joints for the (a) normal, (b) static, and (c) optimal cases

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Fig. 5

Optimal trajectories for the cases of: (a) normal (unbalanced), (b) static, and (c) optimal

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