Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Seyed Mojtaba Karbasi"'
Publikováno v:
Frontiers in Robotics and AI, Vol 11 (2024)
This paper investigates the potential of the intrinsically motivated reinforcement learning (IMRL) approach for robotic drumming. For this purpose, we implemented an IMRL-based algorithm for a drumming robot called ZRob, an underactuated two-DoF robo
Externí odkaz:
https://doaj.org/article/f636229f97f047b4af48f8c35f642da7
Autor:
Seyed MohammadReza Sajadi, Seyed Mojtaba Karbasi, Henrik Brun, Jim Tørresen, Ole Jacob Elle, Kim Mathiassen
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
This paper presents the design, control, and experimental evaluation of a novel fully automated robotic-assisted system for the positioning and insertion of a commercial full core biopsy instrument under guidance by ultrasound imaging. The robotic sy
Externí odkaz:
https://doaj.org/article/647bdb3f459e4bb3a8603979e37fb28c
Autor:
Markus Toverud Ruud, Tale Hisdal Sandberg, Ulrik Johan Vedde Tranvaag, Benedikte Wallace, Seyed Mojtaba Karbasi, Jim Torresen
Generating genuinely creative and novel artifacts with machine learning is still a challenge in the world of computational science. A creative machine learning agent can be beneficial for applications where novel solutions are desired and may also op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::39a581a2a3a1fcfb44c8d88c13053ac5
http://hdl.handle.net/10852/95046
http://hdl.handle.net/10852/95046
Publikováno v:
ICMRE
In robot drumming, performing double stroke rolls is a key ability. Human drummers learn to play double strokes by just trying it several times. For performing it, a model needs to be learned to provide anticipatory commands during drumming. Joint st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d9143ae958b1127942981810cc0d12c
https://doi.org/10.1109/icmre51691.2021.9384843
https://doi.org/10.1109/icmre51691.2021.9384843