ORB-SLAM accelerated on heterogeneous parallel architectures
| Autor: | Mohamed Abouzahir, Rachid Latif, Ayoub Mamri, Mustapha Ramzi |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
lcsh:GE1-350
0209 industrial biotechnology Computer science business.industry 02 engineering and technology Simultaneous localization and mapping Program optimization Software_PROGRAMMINGTECHNIQUES CUDA 020901 industrial engineering & automation Embedded system 0202 electrical engineering electronic engineering information engineering Robot 020201 artificial intelligence & image processing General-purpose computing on graphics processing units business Field-programmable gate array lcsh:Environmental sciences Orb (optics) Block (data storage) ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | E3S Web of Conferences, Vol 229, p 01055 (2021) |
| ISSN: | 2267-1242 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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