Pregled bibliografske jedinice broj: 1162133
Soft robotics approach to autonomous plastering
Soft robotics approach to autonomous plastering // 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)
Lyon, Francuska: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 482-487 doi:10.1109/case49439.2021.9551597 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1162133 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Soft robotics approach to autonomous plastering
Autori
Polic, Marsela ; Maric, Bruno ; Orsag, Matko
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
ISBN
978-1-6654-1873-7
Skup
2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)
Mjesto i datum
Lyon, Francuska, 23.08.2021. - 27.08.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Deep learning , Service robots , Neural networks , Transfer learning , Estimation , Tools , Soft robotics
(duboko učenje, roboti , neuronske mreže , preneseno učenje , estimacija , alati , meka robotika)
Sažetak
This paper presents an industrial soft robotics application for the autonomous plastering of complex shaped surfaces, using a collaborative industrial manipulator. In the core of the proposed system is the deep learning based soft body modeling, i.e. deformation estimation of the flexible plastering knife tool. The estimation relies on visual feedback and a deep convolution neural network (CNN). The transfer learning approach and specially designed dataset generation procedures were developed in the learning phase. The estimated deformation of the plastering knife is then used to control the knife inclination with respect to the treated surface, as one of the essential control variables in the plastering procedure. The developed system is experimentally validated, including both the CNN based deformation estimation, as well as its performance in the knife inclination control.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
HRZZ-UIP-2017-05-4042 - Strukturiran ekološki uzgoj primjenom autonomnih robota u staklenicima (SPECULARIA) (Orsag, Matko, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
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