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Open AccessArticle

A General-Purpose Graphics Processing Unit (GPGPU)-Accelerated Robotic Controller Using a Low Power Mobile Platform

1
Dipartimento di Automatica e Informatica (DAUIN), Politecnico di Torino, 10129 Turin, Italy
2
Department of Electrical Engineering, University of Central Punjab, 54770 Lahore, Pakistan
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Authors to whom correspondence should be addressed.
This paper is an extended version of our paper published in Proceedings of the International Conference on Development and Application Systems (DAS’16) as S. T. H. Rizvi, G. Cabodi, D. Patti and M. M. Gulzar, “Comparison of GPGPU based robotic manipulator with other embedded controllers”, 2016 International Conference on Development and Application Systems (DAS’16), Suceava, Romania, 19–21 May 2016; pp. 10–15.
Academic Editor: Alexander Fish
J. Low Power Electron. Appl. 2017, 7(2), 10; https://doi.org/10.3390/jlpea7020010
Received: 9 March 2017 / Revised: 27 April 2017 / Accepted: 29 April 2017 / Published: 5 May 2017
Robotic controllers have to execute various complex independent tasks repeatedly. Massive processing power is required by the motion controllers to compute the solution of these computationally intensive algorithms. General-purpose graphics processing unit (GPGPU)-enabled mobile phones can be leveraged for acceleration of these motion controllers. Embedded GPUs can replace several dedicated computing boards by a single powerful and less power-consuming GPU. In this paper, the inverse kinematic algorithm based numeric controllers is proposed and realized using the GPGPU of a handheld mobile device. This work is the extension of a desktop GPU-accelerated robotic controller presented at DAS’16 where the comparative analysis of different sequential and concurrent controllers is discussed. First of all, the inverse kinematic algorithm is sequentially realized using Arduino-Due microcontroller and the field-programmable gate array (FPGA) is used for its parallel implementation. Execution speeds of these controllers are compared with two different GPGPU architectures (Nvidia Quadro K2200 and Nvidia Shield K1 Tablet), programmed with Compute Unified Device Architecture (CUDA) computing language. Experimental data shows that the proposed mobile platform-based scheme outperforms the FPGA by 5× and boasts a 100× speedup over the Arduino-based sequential implementation. View Full-Text
Keywords: concurrent computing; manipulators; mobile computing; performance analysis; inverse kinematic; microcontroller; field-programmable gate array (FPGA); general-purpose graphics processing unit (GPGPU) concurrent computing; manipulators; mobile computing; performance analysis; inverse kinematic; microcontroller; field-programmable gate array (FPGA); general-purpose graphics processing unit (GPGPU)
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Rizvi, S.T.H.; Cabodi, G.; Patti, D.; Gulzar, M.M. A General-Purpose Graphics Processing Unit (GPGPU)-Accelerated Robotic Controller Using a Low Power Mobile Platform . J. Low Power Electron. Appl. 2017, 7, 10.

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