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

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

Eduardo A. Gerlein;Gabriel Díaz-Guevara;Henry Carrillo;Carlos Parra;Enrique Gonzalez;Gerlein, Eduardo A.;Díaz-Guevara, Gabriel;Carrillo, Henry;Parra, Carlos;Gonzalez, Enrique;
Electronics 2021 Vol. 10 pp. 1378-
178
gerlein2021electronicsembbedded

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.

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