Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Bharana Fernando"'
Autor:
Shawhin Talebi, David J. Lary, Lakitha O. H. Wijeratne, Bharana Fernando, Tatiana Lary, Matthew Lary, John Sadler, Arjun Sridhar, John Waczak, Adam Aker, Yichao Zhang
Publikováno v:
Sensors, Vol 22, Iss 11, p 4240 (2022)
The human body is an incredible and complex sensing system. Environmental factors trigger a wide range of automatic neurophysiological responses. Biometric sensors can capture these responses in real time, providing clues about the underlying biophys
Externí odkaz:
https://doaj.org/article/a176b21c44f94605ad470d053c9d18eb
Autor:
David J. Lary, David Schaefer, John Waczak, Adam Aker, Aaron Barbosa, Lakitha O. H. Wijeratne, Shawhin Talebi, Bharana Fernando, John Sadler, Tatiana Lary, Matthew D. Lary
Publikováno v:
Sensors, Vol 21, Iss 6, p 2240 (2021)
This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The flexible paradigm is easily scalable to multi-robot, multi-sensor autonomous teams, and it
Externí odkaz:
https://doaj.org/article/058e16eaf51c4a19882447a74d0e59e6
Autor:
Shawhin Talebi, David Lary, Lakitha Wijeratne, Bharana Fernando, Tatiana Lary, Matthew Lary, John Sadler, Arjun Srid, John Waczak, Adam Aker, Yichao Zhang
The human body is an incredible and complex sensing system. Environmental factors trigger a wide range of automatic neurophysiological responses. Biometric sensors can capture these responses in real time, providing clues to the underlying biophysica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d078a773027e57cba1a9b2a7314a1998
https://doi.org/10.21203/rs.3.rs-1499191/v1
https://doi.org/10.21203/rs.3.rs-1499191/v1
Autor:
John Z. Sadler, Shawhin Talebi, John Waczak, David J. Lary, Matthew D. Lary, Aaron Barbosa, Tatiana Lary, Bharana Fernando, Lakitha O. H. Wijeratne, David Schaefer, Adam R. Aker
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 21
Issue 6
Sensors, Vol 21, Iss 2240, p 2240 (2021)
Sensors
Volume 21
Issue 6
Sensors, Vol 21, Iss 2240, p 2240 (2021)
This paper describes and demonstrates an autonomous robotic team that can rapidly learn the characteristics of environments that it has never seen before. The flexible paradigm is easily scalable to multi-robot, multi-sensor autonomous teams, and it
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88c8837bbef18c3ef48bd0d9a2865be9
https://doi.org/10.20944/preprints202102.0454.v1
https://doi.org/10.20944/preprints202102.0454.v1