Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sabrina J. Abram"'
Autor:
Navvab Kashiri, Andy Abate, Sabrina J. Abram, Alin Albu-Schaffer, Patrick J. Clary, Monica Daley, Salman Faraji, Raphael Furnemont, Manolo Garabini, Hartmut Geyer, Alena M. Grabowski, Jonathan Hurst, Jorn Malzahn, Glenn Mathijssen, David Remy, Wesley Roozing, Mohammad Shahbazi, Surabhi N. Simha, Jae-Bok Song, Nils Smit-Anseeuw, Stefano Stramigioli, Bram Vanderborght, Yevgeniy Yesilevskiy, Nikos Tsagarakis
Publikováno v:
Frontiers in Robotics and AI, Vol 5 (2018)
Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of ener
Externí odkaz:
https://doaj.org/article/52835f66c564432b81125db1f6ab12f1
Publikováno v:
PLoS Computational Biology, Vol 20, Iss 4, p e1011951 (2024)
Implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors to keep the sensorimotor system precisely calibrated. This hypothesis has been challenged by recent evidence suggesting flexibility in
Externí odkaz:
https://doaj.org/article/0b6b74ef74934f3b8230c07ebdc5642a
Cerebellar-dependent implicit adaptation has been regarded as a rigid process that automatically operates in response to movement errors in order to keep the sensorimotor system calibrated. This hypothesis has been challenged by recent evidence sugge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf20b71bd0f17a6ee71c61b2728ea658
https://doi.org/10.1101/2023.01.27.525949
https://doi.org/10.1101/2023.01.27.525949
Autor:
Sabrina J. Abram, Katherine L. Poggensee, Natalia Sánchez, Surabhi N. Simha, James M. Finley, Steven H. Collins, J. Maxwell Donelan
Publikováno v:
Curr Biol
Delft University of Technology
Delft University of Technology
Our nervous systems can learn optimal control policies in response to changes to our bodies, tasks, and movement contexts. For example, humans can learn to adapt their control policy in walking contexts where the energy-optimal policy is shifted alon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d71c507e6b80e46fb24806fe63741d30
https://europepmc.org/articles/PMC9504978/
https://europepmc.org/articles/PMC9504978/
Publikováno v:
Journal of neurophysiology. 126(2)
When in a new situation, the nervous system may benefit from adapting its control policy. In determining whether or not to initiate this adaptation, the nervous system may rely on some features of the new situation. Here we tested whether one such fe
People prefer to move in energetically optimal ways during walking. We recently found that this preference arises not just through evolution and development, but that the nervous system will continuously optimize step frequency in response to new ene
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6b11ec0b4a19f550eb4613605839a3df
Autor:
Bram Vanderborght, Andy Abate, Monica A. Daley, Salman Faraji, Raphael Furnemont, Manolo Garabini, Stefano Stramigioli, Hartmut Geyer, Sabrina J. Abram, Mohammad Shahbazi, Yevgeniy Yesilevskiy, C. David Remy, Alin Albu-Schaffer, Wesley Roozing, Patrick Clary, Jonathan W. Hurst, Nikolaos G. Tsagarakis, Surabhi N. Simha, Glenn Mathijssen, Navvab Kashiri, Nils Smit-Anseeuw, Jae-Bok Song, Alena M. Grabowski, Jorn Malzahn
Publikováno v:
Frontiers in Robotics and AI, Vol 5 (2018)
Frontiers in Robotics and AI
Frontiers in robotics and AI, vol 5, iss DEC
Frontiers in Robotics and AI
Frontiers in robotics and AI, vol 5, iss DEC
Despite enhancements in the development of robotic systems, the energy economy of today's robots lags far behind that of biological systems. This is in particular critical for untethered legged robot locomotion. To elucidate the current stage of ener