Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM

Gerlein, Eduardo A.; Díaz-Guevara, Gabriel; Carrillo, Henry; Parra, Carlos; Gonzalez, Enrique

doi:10.3390/electronics10121378

Open AccessArticle

Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM

by

Eduardo A. Gerlein

^1,*

,

Gabriel Díaz-Guevara

¹

,

Henry Carrillo

²

,

Carlos Parra

¹

and

Enrique Gonzalez

³

¹

Department of Electronics, Pontificia Universidad Javeriana, Bogotá 110231, Colombia

²

Genius Sports, Medellin 050022, Colombia

³

Department of Systems Engineering, Pontificia Universidad Javeriana, Bogotá 110231, Colombia

^*

Author to whom correspondence should be addressed.

Electronics 2021, 10(12), 1378; https://doi.org/10.3390/electronics10121378

Submission received: 15 April 2021 / Revised: 13 May 2021 / Accepted: 21 May 2021 / Published: 9 June 2021

(This article belongs to the Section Computer Science & Engineering)

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Abstract

This paper discusses a novel embedded system-on-chip 3D localization and mapping (eSoC-LAM) implementation, that followed a co-design approach with the primary aim of being deployed in a small system on a programmable chip (SoPC), the Intel’s (a.k.a Altera) Cyclone V 5CSEMA5F31C6N, available in the Terasic’s board DE1-SoC. This computer board incorporates an 800 MHz Dual-core ARM Cortex-A9 and a Cyclone V FPGA with 85k programmable logic elements and 4450 Kbits of embedded memory running at 50 MHz. We report experiments of the eSoC-LAM implementation using a Robosense’s 3D LiDAR RS-16 sensor in a Robotis’ TurtleBot2 differential robot, both controlled by a Terasic’s board DE1-SoC. This paper presents a comprehensive description of the designed architecture, design constraints, resource optimization, HPS-FPGA exchange of information, and co-design results. The eSoC-LAM implementation reached an average speed-up of 6.5× when compared with a version of the algorithm running in a the hard processor system of the Cyclone V device, and a performance of nearly 32 fps, while keeping high map accuracy.

Keywords: system-on-chip; SoC; SoPC; FPGA; SLAM; robot localization; robot mapping; hardware architecture; embedded robotics

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MDPI and ACS Style

Gerlein, E.A.; Díaz-Guevara, G.; Carrillo, H.; Parra, C.; Gonzalez, E. Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM. Electronics 2021, 10, 1378. https://doi.org/10.3390/electronics10121378

AMA Style

Gerlein EA, Díaz-Guevara G, Carrillo H, Parra C, Gonzalez E. Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM. Electronics. 2021; 10(12):1378. https://doi.org/10.3390/electronics10121378

Chicago/Turabian Style

Gerlein, Eduardo A., Gabriel Díaz-Guevara, Henry Carrillo, Carlos Parra, and Enrique Gonzalez. 2021. "Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM" Electronics 10, no. 12: 1378. https://doi.org/10.3390/electronics10121378

APA Style

Gerlein, E. A., Díaz-Guevara, G., Carrillo, H., Parra, C., & Gonzalez, E. (2021). Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM. Electronics, 10(12), 1378. https://doi.org/10.3390/electronics10121378

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Embbedded System-on-Chip 3D Localization and Mapping—eSoC-SLAM

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