Probabilistic self-localisation on a qualitative map based on occlusions
- Submitting institution
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Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 21866452
- Type
- D - Journal article
- DOI
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10.1080/0952813X.2015.1132265
- Title of journal
- Journal of Experimental & Theoretical Artificial Intelligence
- Article number
- -
- First page
- 781
- Volume
- 28
- Issue
- 5
- ISSN
- 0952-813X
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 4
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper integrates robot localisation (using RGB-D camera data) within a probabilistic framework to localise the robot within a novel qualitative model. Being able to describe location qualitatively brings us a step closer to natural interaction between robots and humans. Cited by internationally recognised researchers from Australia, Brazil, France, Germany, Spain, Switzerland, Venezuela.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -