Optimization Of Energy Consumption In KUKA KR 16 Articulated Robot Manipulator

Mohd Shah, Hairol Nizam and Sulaiman, Marizan and Mohamad Isa, Kamarul Syaffiq and Kamis, Zalina and Baharon, Mohd Rizuan (2019) Optimization Of Energy Consumption In KUKA KR 16 Articulated Robot Manipulator. International Journal of Recent Technology and Engineering, 8 (3). pp. 6470-6476. ISSN 2277-3878

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Abstract

A study for optimal energy consumption in KUKA KR 16 articulated robot for pick-and-place task was introduce in this paper. In order to achieve the optimal energy consumption, an improve trajectory planning is required. Essentially, trajectory planning encompasses path planning in addition to planning how to move based on velocity, time and kinematics. Trajectory planning gives a path from a starting to a goal point by avoiding collisions in a 2D or 3D space. Therefore, this paper is focus on analyze the PTP motion and Linear motion in order to determine which is the best motion that can improve the trajectory planning. The optimal energy consumption to minimizing the movement based on three main axes where it used a big motors used to drive the axes. This method is much simpler in terms of development process and did not require any additional hardware to be install to the robot’s system. KUKA KR 16 is use to study optimal energy consumption and analyze PTP and Linear motion. The energy performance is measures with respect to two categories of movements known as Default and Optimal movement which do the same task repetitively within specific time. The result show that PTP motion consumed 6% more energy than Linear motion but completed 773 cycles within one hour whereas Linear motion only completed 492 cycles. Energy performance between Default and Optimal movement shows that Optimal movement recorded 21.8% less energy usage when compared to Default movement although the total cycles completed for both movement almost the same.

Item Type:	Article
Uncontrolled Keywords:	Energy consumption, Joints movement, KUKA KR 16, Optimal energy
Divisions:	Faculty of Electrical Engineering
Depositing User:	Sabariah Ismail
Date Deposited:	08 Dec 2020 15:01
Last Modified:	08 Dec 2020 15:01
URI:	http://eprints.utem.edu.my/id/eprint/24631
Statistic Details:	View Download Statistic

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