Learning Context on a Humanoid Robot using Incremental Latent Dirichlet Allocation
- Submitting institution
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The University of Surrey
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 9027031_3
- Type
- D - Journal article
- DOI
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10.1109/TAMD.2015.2476374
- Title of journal
- IEEE Transactions on Cognitive and Developmental Systems
- Article number
- -
- First page
- 42-59
- Volume
- 8
- Issue
- 1
- ISSN
- 2379-8920
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2015
- URL
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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-
- Research group(s)
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- Citation count
- 12
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Winner of 2019 IEEE TCDS Outstanding Paper Award: https://cis.ieee.org/getting-involved/awards/past-recipients. While there are examples of cognitive modelling in existence, which model for the sake of understanding, few take psychology ideas and show they bring advantages to practical robotics problems. The work was the basis for several grant submissions to EU Horizon 2020 with Tesco UK for a project featuring robots replenishing shelves in a supermarket alongside human staff, hence making it important to respond appropriately to the context, as addressed in the paper. The link with Tesco was subsequently used for an EPSRC submission with Tesco as partner.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -