Development of a low-cost SLAM radar for applications in robotics.
Irps, Thomas, Prior, Stephen D., Lewis, Darren, Mielniczek, Witold, Brazinskas, Mantas, Barlow, Chris and Karamanoglu, Mehmet ORCID: https://orcid.org/0000-0002-5049-2993
(2010)
Development of a low-cost SLAM radar for applications in robotics.
International Conference on Manufacturing Engineering Systems, 2010
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pp. 299-304.
ISSN 2152-1522
[Article]
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Abstract
The current state of SLAM radar is quite advanced, featuring various methods of data retrieval. One of the methods used is that of video telemetry to locate “common spots” in the surrounding environment which provide positional information during motion. Another method is that of using high-speed high-resolution laser measurement tools which provide a 360° horizontal field of view and a 90° vertical field of view. These systems create vast amounts of point cloud data and are expensive, ranging from £1,000 upwards. These systems are often unsuitable for small competition robots due to these reasons.
The developments discussed in this paper describes various alternative measurement technologies, such as ultrasonic and infra-red and how these can be adapted with the addition of a mechanical drive to provide an almost real-time 360° horizontal field of view and an adjustable vertical field of view.
Item Type: | Article |
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Additional Information: | International Conference on Manufacturing Engineering Systems conference held at South Taiwan University on 16-20th Dec 2010. |
Keywords (uncontrolled): | Mobile Robotics, SLAM, Mapping. |
Research Areas: | A. > School of Science and Technology > Design Engineering and Mathematics |
Item ID: | 6902 |
Notes on copyright: | With thanks to publisher for permitting reproduction of article. |
Useful Links: | |
Depositing User: | Dr Stephen Prior |
Date Deposited: | 20 Jan 2011 11:46 |
Last Modified: | 30 Nov 2022 01:11 |
URI: | https://eprints.mdx.ac.uk/id/eprint/6902 |
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- Development of a low-cost SLAM radar for applications in robotics. (deposited 20 Jan 2011 11:46) [Currently Displayed]
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