Navigating the landscape for real-time localisation and mapping for robotics, virtual and augmented reality
File(s)08436423.pdf (2.73 MB)
Published version
Author(s)
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.
Date Issued
2018-11
Date Acceptance
2018-06-29
Citation
Proceedings of the IEEE, 2018, 106 (11), pp.2020-2039
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
Engineering & Physical Science Research Council (E
Identifier
https://ieeexplore.ieee.org/document/8436423
Grant Number
PO: ERZ1820653
Subjects
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
OA Location
https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8436423
Date Publish Online
2018-08-14