Zobrazeno 1 - 10
of 471
pro vyhledávání: '"Doherty, Kevin"'
Autor:
Doherty, Kevin, Kallina, Emma, Moylan, Kayley, Silva, María Paula, Karimian, Sajjad, Shumsher, Shivam, Brennan, Rob
We find ourselves on the ever-shifting cusp of an AI revolution -- with potentially metamorphic implications for the future practice of healthcare. For many, such innovations cannot come quickly enough; as healthcare systems worldwide struggle to kee
Externí odkaz:
http://arxiv.org/abs/2411.02067
Simultaneous localization and mapping (SLAM) is a critical capability in autonomous navigation, but memory and computational limits make long-term application of common SLAM techniques impractical; a robot must be able to determine what information s
Externí odkaz:
http://arxiv.org/abs/2403.19879
Autor:
Doherty, Kevin J.
Simultaneous localization and mapping (SLAM) is the process by which a robot constructs a global model of an environment from local observations of it; this is a fundamental perceptual capability supporting planning, navigation, and control. We are i
Externí odkaz:
https://hdl.handle.net/1721.1/150281
Publikováno v:
Journal of Computational Physics, Volume 498, 1 February 2024
We present a new convolution layer for deep learning architectures which we call QuadConv -- an approximation to continuous convolution via quadrature. Our operator is developed explicitly for use on non-uniform, mesh-based data, and accomplishes thi
Externí odkaz:
http://arxiv.org/abs/2211.05151
We present a novel initialization technique for the range-aided simultaneous localization and mapping (RA-SLAM) problem. In RA-SLAM we consider measurements of point-to-point distances in addition to measurements of rigid transformations to landmark
Externí odkaz:
http://arxiv.org/abs/2210.03177
We describe a general approach for maximum a posteriori (MAP) inference in a class of discrete-continuous factor graphs commonly encountered in robotics applications. While there are openly available tools providing flexible and easy-to-use interface
Externí odkaz:
http://arxiv.org/abs/2204.11936
Simultaneous localization and mapping (SLAM) is a critical capability in autonomous navigation, but in order to scale SLAM to the setting of "lifelong" SLAM, particularly under memory or computation constraints, a robot must be able to determine what
Externí odkaz:
http://arxiv.org/abs/2203.13897
Recent progress in object pose prediction provides a promising path for robots to build object-level scene representations during navigation. However, as we deploy a robot in novel environments, the out-of-distribution data can degrade the prediction
Externí odkaz:
http://arxiv.org/abs/2203.04424
Autor:
Prochazka, Brian G., Lundblad, Carl G., Doherty, Kevin E., O'Neil, Shawn T., Tull, John C., Abele, Steve C., Aldridge, Cameron L., Coates, Peter S.
Publikováno v:
In Rangeland Ecology & Management November 2024 97:146-159
Autor:
Sparklin, Bill D., Doherty, Kevin E., Rodhouse, Thomas J., Lonneker, Jeffrey J., Spaak, Jordan, Cross, Todd B., Warren, Jeffrey M.
Publikováno v:
In Rangeland Ecology & Management November 2024 97:94-106