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Visual Appearance Analysis of Forest Scenes for Monocular SLAM

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https://ieeexplore.ieee.org/document/8793771
Original languageEnglish
Title of host publication2019 International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1794-1800
Number of pages7
ISBN (Electronic)978-1-5386-6027-0
ISBN (Print)978-1-5386-8176-3
DOIs
Publication statusPublished - 12 Aug 2019
Event2019 IEEE International Conference on Robotics and Automation (ICRA) - Montreal, Canada
Duration: 20 May 201924 May 2019
https://www.icra2019.org/

Publication series

Name
PublisherInstitute of Electrical and Electronics Engineers
ISSN (Print)1050-4729
ISSN (Electronic)2577-087X

Conference

Conference2019 IEEE International Conference on Robotics and Automation (ICRA)
Abbreviated titleICRA 2019
CountryCanada
CityMontreal
Period20/05/1924/05/19
Internet address

Abstract

Monocular simultaneous localisation and mapping (SLAM) is a cheap and energy efficient way to enable Unmanned Aerial Vehicles (UAVs) to safely navigate managed forests and gather data crucial for monitoring tree health. SLAM research, however, has mostly been conducted in structured human environments, and as such is poorly adapted to unstructured forests. In this paper, we compare the performance of state of the art monocular SLAM systems on forest data and use visual appearance statistics to characterise the differences between forests and other environments, including a photorealistic simulated forest. We find that SLAM systems struggle with all but the most straightforward forest terrain and identify key attributes (lighting changes and in-scene motion) which distinguish forest scenes from “classic” urban datasets. These differences offer an insight into what makes forests harder to map and open the way for targeted improvements. We also demonstrate that even simulations that look impressive to the human eye can fail to properly reflect the difficult attributes of the environment they simulate, and provide suggestions for
more closely mimicking natural scenes.

Event

2019 IEEE International Conference on Robotics and Automation (ICRA)

20/05/1924/05/19

Montreal, Canada

Event: Conference

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