دورية أكاديمية

Cut & recombine: reuse of robot action components based on simple language instructions

التفاصيل البيبلوغرافية
العنوان: Cut & recombine: reuse of robot action components based on simple language instructions
المؤلفون: Tamošiūnaitė, Minija, Aein, Mohamad Javad, Braun, Jan Matthias, Kulvičius, Tomas, Markievicz, Irena, Kapočiūtė-Dzikienė, Jurgita, Valterytė, Rita, Haidu, Andrei, Chrysostomou, Dimitrios, Ridge, Barry, Krilavičius, Tomas, Vitkutė-Adžgauskienė, Daiva, Beetz, Michael, Madsen, Ole, Ude, Ales, Krüger, Norbert, Wörgötter, Florentin
سنة النشر: 2019
المجموعة: Vytautas Magnus University e-Publication Repository (VMU ePub) / Vytauto Didžiojo universitetas: e. publikacijų talpykla (VDU ePub)
مصطلحات موضوعية: Service robotics, Cognitive robotics, Manipulation planning, Control architectures and programming, Straipsnis Clarivate Analytics Web of Science / Article in Clarivate Analytics Web of Science (S1), Informatika / Informatics (N009)
جغرافية الموضوع: GB
الوصف: Human beings can generalize from one action to similar ones. Robots cannot do this and progress concerning information transfer between robotic actions is slow. We have designed a system that performs action generalization for manipulation actions in different scenarios. It relies on an action representation for which we perform code-snippet replacement, combining information from different actions to form new ones. The system interprets human instructions via a parser using simplified language. It uses action and object names to index action data tables (ADTs), where execution-relevant information is stored. We have created an ADT database from three different sources (KUKA LWR, UR5, and simulation) and show how a new ADT is generated by cutting and recombining data from existing ADTs. To achieve this, a small set of action templates is used. After parsing a new instruction, index-based searching finds similar ADTs in the database. Then the action template of the new action is matched against the information in the similar ADTs. Code snippets are extracted and ranked according to matching quality. The new ADT is created by concatenating code snippets from best matches. For execution, only coordinate transforms are needed to account for the poses of the objects in the new scene. The system was evaluated, without additional error correction, using 45 unknown objects in 81 new action executions, with 80% success. We then extended the method including more detailed shape information, which further reduced errors. This demonstrates that cut & recombine is a viable approach for action generalization in service robotic applications ; Sistemų analizės katedra ; Taikomosios informatikos katedra ; Vytauto Didžiojo universitetas
نوع الوثيقة: article in journal/newspaper
وصف الملف: p. 1179-1207; application/pdf
اللغة: English
تدمد: 02783649
العلاقة: International journal of robotics research. London: Sage publications, 2019, Vol. 38, iss. 10-11; Science Citation Index Expanded (Web of Science); Scopus; Sage Premier; VDU02-000061588; https://www.vdu.lt/cris/bitstream/20.500.12259/101519/2/ISSN1741-3176_2019_V_38_10-11.PG_1179-1207.pdfTest; https://hdl.handle.net/20.500.12259/101519Test; https://doi.org/10.1177/0278364919865594Test; WOS:000479795100001
DOI: 10.1177/0278364919865594
الإتاحة: https://doi.org/20.500.12259/101519Test
https://doi.org/10.1177/0278364919865594Test
https://www.vdu.lt/cris/bitstream/20.500.12259/101519/2/ISSN1741-3176_2019_V_38_10-11.PG_1179-1207.pdfTest
https://hdl.handle.net/20.500.12259/101519Test
حقوق: https://creativecommons.org/licenses/by-nc/4.0Test/
رقم الانضمام: edsbas.83A06C42
قاعدة البيانات: BASE
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