Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Noémie Jaquier"'
Publikováno v:
Technologies, Vol 5, Iss 4, p 64 (2017)
Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study th
Externí odkaz:
https://doaj.org/article/2eca738f8ffe43e784d8bf2996810a4b
Autor:
Noémie Jaquier, Tamim Asfour
Publikováno v:
Springer Proceedings in Advanced Robotics ISBN: 9783031255540
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::55cc9b65a82e314374bf234578edfdb7
https://doi.org/10.1007/978-3-031-25555-7_27
https://doi.org/10.1007/978-3-031-25555-7_27
Publikováno v:
The International Journal of Robotics Research
Body posture influences human and robots performance in manipulation tasks, as appropriate poses facilitate motion or force exertion along different axes. In robotics, manipulability ellipsoids arise as a powerful descriptor to analyze, control and d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dfd342c8f0e79e92b422d8cabaaeca2a
https://pubmed.ncbi.nlm.nih.gov/33994629
https://pubmed.ncbi.nlm.nih.gov/33994629
Publikováno v:
IROS
Humans exhibit outstanding learning, planning and adaptation capabilities while performing different types of industrial tasks. Given some knowledge about the task requirements, humans are able to plan their limbs motion in anticipation of the execut
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::143176602b2a05ea8498fd164292c518
https://doi.org/10.1109/iros45743.2020.9341353
https://doi.org/10.1109/iros45743.2020.9341353
Publikováno v:
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
IROS
IROS
Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a great influence on the generalization performances of LfD approaches. In t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7dbe7100fea628fc5668d3abd6135259
When data are organized in matrices or arrays of higher dimensions (tensors), classical regression methods first transform these data into vectors, therefore ignoring the underlying structure of the data and increasing the dimensionality of the probl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4c1e1afc6b480473d7e0c85e2bfd0c8
http://arxiv.org/abs/1902.11104
http://arxiv.org/abs/1902.11104
Publikováno v:
Robotics: Science and Systems
Body posture can greatly influence human performance when carrying out manipulation tasks. Adopting an appropriate pose helps us regulate our motion and strengthen our capability to achieve a given task. This effect is also observed in robotic manipu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::052f4682c0d597ea5139dd5ca546a08b
https://doi.org/10.15607/rss.2018.xiv.027
https://doi.org/10.15607/rss.2018.xiv.027
Autor:
Sylvain Calinon, Noémie Jaquier
Publikováno v:
IROS
In many sensing and control applications, data are represented in the form of symmetric positive definite (SPD) matrices. Considering the underlying geometry of this data space can be beneficial in many robotics applications. In this paper, we presen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c76d45ad30014d414904142ce71174a
https://doi.org/10.1109/iros.2017.8202138
https://doi.org/10.1109/iros.2017.8202138
Publikováno v:
IROS
Posture body variation is one of the ways in which humans skillfully and naturally augment their motion and strength capabilities along specific task-space directions in order to successfully perform complex manipulation tasks. Posture variation also
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fa204e7c5b2fc572a409c7615352f597
https://doi.org/10.1109/iros.2017.8206150
https://doi.org/10.1109/iros.2017.8206150