Imperial College London
Alternate

ProfessorChristos-SavvasBouganis

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Intelligent Digital Systems
 
 
 
//

Contact

 

+44 (0)20 7594 6144christos-savvas.bouganis Website

 
 
//

Location

 

904Electrical EngineeringSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Boikos:2019:10.1007/978-3-030-17227-5_14,
author = {Boikos, K and Bouganis, C-S},
doi = {10.1007/978-3-030-17227-5_14},
pages = {181--196},
publisher = {Springer},
title = {A scalable FPGA-based architecture for depth estimation in SLAM},
url = {http://dx.doi.org/10.1007/978-3-030-17227-5_14},
year = {2019}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The current state of the art of Simultaneous Localisation and Mapping, or SLAM, on low power embedded systems is about sparse localisation and mapping with low resolution results in the name of efficiency. Meanwhile, research in this field has provided many advances for information rich processing and semantic understanding, combined with high computational requirements for real-time processing. This work provides a solution to bridging this gap, in the form of a scalable SLAM-specific architecture for depth estimation for direct semi-dense SLAM. Targeting an off-the-shelf FPGA-SoC this accelerator architecture achieves a rate of more than 60 mapped frames/sec at a resolution of 640×480 achieving performance on par to a highly-optimised parallel implementation on a high-end desktop CPU with an order of magnitude improved power consumption. Furthermore, the developed architecture is combined with our previous work for the task of tracking, to form the first complete accelerator for semi-dense SLAM on FPGAs, establishing the state of the art in the area of embedded low-power systems.
AU  - Boikos,K
AU  - Bouganis,C-S
DO  - 10.1007/978-3-030-17227-5_14
EP  - 196
PB  - Springer
PY  - 2019///
SP  - 181
TI  - A scalable FPGA-based architecture for depth estimation in SLAM
UR  - http://dx.doi.org/10.1007/978-3-030-17227-5_14
UR  - http://arxiv.org/abs/1902.04907v1
UR  - http://hdl.handle.net/10044/1/74924
ER  -
Download