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Pregled bibliografske jedinice broj: 1037485

Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization


Vidaković, Josip; Jerbić, Bojan; Šekoranja, Bojan; Švaco, Marko; Šuligoj, Filip
Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization // Journal of intelligent & robotic systems, 96 (2019), 1-15 doi:10.1007/s10846-019-01101-2 (međunarodna recenzija, članak, znanstveni)


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Naslov
Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization

Autori
Vidaković, Josip ; Jerbić, Bojan ; Šekoranja, Bojan ; Švaco, Marko ; Šuligoj, Filip

Izvornik
Journal of intelligent & robotic systems (0921-0296) 96 (2019); 1-15

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Learning from demonstration ; Task parameterized movement ; Trajectory optimization ; Robot trajectory

Sažetak
Learning from demonstration involves the extraction of important information from demonstrations and the reproduction of robot action sequences or trajectories with generalization capabilities. Task parameters represent certain dependencies observed in demonstrations used to constrain and define a robot action because of the infinite nature of the state-space environment. We present the methodology for learning from demonstration based on a classification of task parameters. The classified task parameters are used to construct a cost function, responsible for describing the demonstration data. For reproduction we propose a novel trajectory optimization that is able to generate a simplified version of the trajectory for different configurations of the task parameters. As the last step before reproduction on a real robotic arm we approximate this trajectory with a Dynamic movement primitive (DMP) - based system to retrieve a smooth trajectory. Results obtained for trajectories with three degrees of freedom (two translations and one rotation) show that the system is able to encode multiple task parameters from a low number of demonstrations and generate trajectories that are collision free.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Strojarstvo



POVEZANOST RADA


Projekti:
DOK-2015-10-3073

Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb

Poveznice na cjeloviti tekst rada:

doi link.springer.com

Citiraj ovu publikaciju:

Vidaković, Josip; Jerbić, Bojan; Šekoranja, Bojan; Švaco, Marko; Šuligoj, Filip
Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization // Journal of intelligent & robotic systems, 96 (2019), 1-15 doi:10.1007/s10846-019-01101-2 (međunarodna recenzija, članak, znanstveni)
Vidaković, J., Jerbić, B., Šekoranja, B., Švaco, M. & Šuligoj, F. (2019) Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization. Journal of intelligent & robotic systems, 96, 1-15 doi:10.1007/s10846-019-01101-2.
@article{article, year = {2019}, pages = {1-15}, DOI = {10.1007/s10846-019-01101-2}, keywords = {Learning from demonstration, Task parameterized movement, Trajectory optimization, Robot trajectory}, journal = {Journal of intelligent and robotic systems}, doi = {10.1007/s10846-019-01101-2}, volume = {96}, issn = {0921-0296}, title = {Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization}, keyword = {Learning from demonstration, Task parameterized movement, Trajectory optimization, Robot trajectory} }
@article{article, year = {2019}, pages = {1-15}, DOI = {10.1007/s10846-019-01101-2}, keywords = {Learning from demonstration, Task parameterized movement, Trajectory optimization, Robot trajectory}, journal = {Journal of intelligent and robotic systems}, doi = {10.1007/s10846-019-01101-2}, volume = {96}, issn = {0921-0296}, title = {Learning from Demonstration Based on a Classification of Task Parameters and Trajectory Optimization}, keyword = {Learning from demonstration, Task parameterized movement, Trajectory optimization, Robot trajectory} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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