Zobrazeno 1 - 6
of 6
pro vyhledávání: '"'Michele Ginesi"'
Publikováno v:
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020)
IROS
IROS
We introduce ImitationFlow, a novel Deep generative model that allows learning complex globally stable, stochastic, nonlinear dynamics. Our approach extends the Normalizing Flows framework to learn stable Stochastic Differential Equations. We prove t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9bd72dd62c0196cc7bd8f441b06d503a
https://hdl.handle.net/21.11116/0000-000B-0579-8
https://hdl.handle.net/21.11116/0000-000B-0579-8
Publikováno v:
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
IROS
IROS
The use of robots in minimally invasive surgery has improved the quality of standard surgical procedures. So far, only the automation of simple surgical actions has been investigated by researchers, while the execution of structured tasks requiring r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6d3e3dfc2d7d43c2404eccded1c9064
http://arxiv.org/abs/2004.08911
http://arxiv.org/abs/2004.08911
Publikováno v:
2019 19th International Conference on Advanced Robotics (ICAR)
ICAR
ICAR
Robotic surgery has significantly improved the quality of surgical procedures. In the past, researches have been focused on automating simple surgical actions. However, there exists no scalable framework for automation in surgery. In this paper, we p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::386f4f7551ea3eab13d017a604742e7f
https://hdl.handle.net/11562/1018544
https://hdl.handle.net/11562/1018544
Autor:
Nicola Sansonetto, Diego Dall'Alba, Andrea Calanca, Daniele Meli, Michele Ginesi, Paolo Fiorini
Publikováno v:
2019 19th International Conference on Advanced Robotics (ICAR)
ICAR
ICAR
Dynamic Movement Primitives (DMPs) are a framework for learning a trajectory from a demonstration. The trajectory can be learned efficiently after only one demonstration, and it is immediate to adapt it to new goal positions and time duration. Moreov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16f1e6198360af3f35dda1d4dc02bf52
http://hdl.handle.net/11562/1018548
http://hdl.handle.net/11562/1018548
Autor:
'Michele Ginesi
Publikováno v:
Nicola Sansonetto
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=r3c4b2081b22::dc107e39bd83cc56fb2b6fb6048ab51b
Publikováno v:
Journal of Intelligent & Robotic Systems. 101(4)
Obstacle avoidance for DMPs is still a challenging problem. In our previous work, we proposed a framework for obstacle avoidance based on superquadric potential functions to represent volumes. In this work, we extend our previous work to include the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::942ad43a9c11d1ea468023ae87ff7299