Keep it Simple: Understanding Natural Language Commands for General-Purpose Service Robots
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A9TRN7YFR" target="_blank" >RIV/00216208:11320/25:9TRN7YFR - isvavai.cz</a>
Result on the web
<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186267003&doi=10.1109%2fSII58957.2024.10417341&partnerID=40&md5=9b80c7bf2bc8da7cdf188ea6c1d648f2" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186267003&doi=10.1109%2fSII58957.2024.10417341&partnerID=40&md5=9b80c7bf2bc8da7cdf188ea6c1d648f2</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SII58957.2024.10417341" target="_blank" >10.1109/SII58957.2024.10417341</a>
Alternative languages
Result language
angličtina
Original language name
Keep it Simple: Understanding Natural Language Commands for General-Purpose Service Robots
Original language description
Service robots are designed to perform useful tasks for humans, which involve managing and combining a variety of skills in the form of global and local plans to solve any given task. In this work, we propose a framework to process natural language commands for general-purpose service robots where the robot should perform an arbitrary spoken command requested by a non-expert operator. Our system uses a Natural Language Processing (NLP) parser and a Conceptual Dependency (CD) builder to create CD structures that an expert system can employ to generate a global plan that the robot will execute. An extra simplification step using Large Language Models (LLM) was tested and evaluated in order to improve the accuracy of the system. Finally, our system has been tested in challenging environments in robot competitions and we have achieved promising results. © 2024 IEEE.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE/SICE Int. Symp. Syst. Integr., SII
ISBN
979-835031207-2
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1320-1325
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
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Event location
Ha Long
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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