Accurate Garment Surface Analysis using an Active Stereo Robot Head with Application to Dual-Arm Flattening
- Submitting institution
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University of Glasgow
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11-01881
- Type
- E - Conference contribution
- DOI
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10.1109/ICRA.2015.7138998
- Title of conference / published proceedings
- IEEE International Conference in Robotics and Automation
- First page
- 185
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- May
- Year of publication
- 2015
- URL
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http://eprints.gla.ac.uk/104927/
- 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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3
- Research group(s)
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-
- Citation count
- 33
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- ORIGINALITY: Presents the first dual-arm robotic manipulator capable of flattening garments autonomously. SIGNIFICANCE: Key contributions are the dual-arm flattening control heuristic and the vision pipeline which fully understands and represents the local structure and state of deformable materials. Received nominations for best paper and best manipulation paper awards, ICRA’15. Received considerable media attention (http://www.bbc.co.uk/news/uk-scotland-32612928), and contributed to securing InnovateUK grant with Shadow Robot Company (£500K) RIGOUR: Defines a complete, geometry-based, classical AI approach to dual-arm clothing flattening in a real robot. Extensive experimental study and demonstration over different flattening and vision and manipulation benchmarks.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -