Navigating the landscape for real-time localisation and mapping for robotics, virtual and augmented reality

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Title: Navigating the landscape for real-time localisation and mapping for robotics, virtual and augmented reality
Authors: Saeedi Gharahbolagh, S
Bodin, B
Wagstaff, H
Nisbet, A
Nardi, L
Mawer, J
Melot, N
Palomar, O
Vespa, E
Gorgovan, C
Webb, A
Clarkson, J
Tomusk, E
Debrunner, T
Kaszyk, K
Gonzalez, P
Rodchenko, A
Riley, G
Kotselidis, C
Franke, B
OBoyle, M
Davison, A
Kelly, P
Lujan, M
Furber, S
Item Type: Journal Article
Abstract: Visual understanding of 3-D environments in real time, at low power, is a huge computational challenge. Often referred to as simultaneous localization and mapping (SLAM), it is central to applications spanning domestic and industrial robotics, autonomous vehicles, and virtual and augmented reality. This paper describes the results of a major research effort to assemble the algorithms, architectures, tools, and systems software needed to enable delivery of SLAM, by supporting applications specialists in selecting and configuring the appropriate algorithm and the appropriate hardware, and compilation pathway, to meet their performance, accuracy, and energy consumption goals. The major contributions we present are: 1) tools and methodology for systematic quantitative evaluation of SLAM algorithms; 2) automated, machine-learning-guided exploration of the algorithmic and implementation design space with respect to multiple objectives; 3) end-to-end simulation tools to enable optimization of heterogeneous, accelerated architectures for the specific algorithmic requirements of the various SLAM algorithmic approaches; and 4) tools for delivering, where appropriate, accelerated, adaptive SLAM solutions in a managed, JIT-compiled, adaptive runtime context.
Issue Date: Nov-2018
Date of Acceptance: 29-Jun-2018
URI: http://hdl.handle.net/10044/1/61930
DOI: https://doi.org/10.1109/JPROC.2018.2856739
ISSN: 0018-9219
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 2020
End Page: 2039
Journal / Book Title: Proceedings of the IEEE
Volume: 106
Issue: 11
Copyright Statement: © 2018 The Author(s). This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
Sponsor/Funder: Engineering & Physical Science Research Council (E
Funder's Grant Number: PO: ERZ1820653
Keywords: Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Automatic performance tuning
hardware simulation
scheduling
simultaneous localization and mapping (SLAM)
PROCESSOR
COMPILATION
CODE
cs.CV
cs.CV
cs.LG
cs.RO
0801 Artificial Intelligence and Image Processing
0903 Biomedical Engineering
0906 Electrical and Electronic Engineering
Publication Status: Published
Open Access location: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8436423
Online Publication Date: 2018-08-14
Appears in Collections:Faculty of Engineering
Computing



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