ORB-SLAM accelerated on heterogeneous parallel architectures

¹ Laboratory of Systems Analysis, Information Processing and Industrial Management, Higher School of Technology of Sale, Mohamed V University of Rabat, Morocco
² Laboratory of Systems Engineering and Information Technology, National School of Applied Sciences, Ibn Zohr University of Agadir, Morocco

^* Ayoub Mamri: ayoub_mamri@um5.ac.ma

Abstract

SLAM algorithm permits the robot to cartography the desired environment while positioning it in space. It is a more efficient system and more accredited by autonomous vehicle navigation and robotic application in the ongoing research. Except it did not adopt any complete end-to-end hardware implementation yet. Our work aims to a hardware/software optimization of an expensive computational time functional block of monocular ORB-SLAM2. Through this, we attempt to implement the proposed optimization in FPGA-based heterogeneous embedded architecture that shows attractive results. Toward this, we adopt a comparative study with other heterogeneous architecture including powerful embedded GPGPU (NVIDIA Tegra TX1) and high-end GPU (NVIDIA GeForce 920MX). The implementation is achieved using high-level synthesis-based OpenCL for FPGA and CUDA for NVIDIA targeted boards.