Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Michael W. Lanighan"'
Publikováno v:
2022 International Conference on Robotics and Automation (ICRA).
Autor:
Seth Gee, Joseph S. Altemus, Jason Lee, Lyndon Bridgwater, Stephen McCrory, Charlie Kendrick, Patrick Beeson, Jairo Sanchez, Joshua S. Mehling, Andrew Watson, Jerry Pratt, R. Scott Askew, Michael W. Lanighan, Robert J. Griffin, Steven Jens Jorgensen, Luis Sentis, Inho Lee, Ana Huaman Quispe, Sylvain Bertrand, Stephen Hart, Beau Domingue, Mark Paterson
Publikováno v:
Humanoids
As part of a feasibility study, this paper shows the NASA Valkyrie humanoid robot performing an end-to-end improvised explosive device (IED) response task. To demonstrate and evaluate robot capabilities, sub-tasks highlight different locomotion, mani
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fabc0a9eddfd494a3d8d7cf3038e5b69
Publikováno v:
IROS
Deep learning has been successful in a variety of applications that have high-dimensional state spaces such as object recognition, video games, and machine translation. Deep neural networks can automatically learn important features from high-dimensi
Autor:
Roderic A. Grupen, Mitchell Hebert, Tiffany Q. Liu, Takeshi Takahashi, Dirk Ruiken, Jay Ming Wong, Michael W. Lanighan
Publikováno v:
IROS
This paper presents an active, model-based recognition system. It applies information theoretic measures in a belief-driven planning framework to recognize objects using the history of visual and manual interactions and to select the most informative
Autor:
Jonathan P. Cummings, Michael W. Lanighan, Frank C. Sup, Dirk Ruiken, Roderic A. Grupen, Eric L. Wilkinson
Publikováno v:
Journal of Mechanisms and Robotics. 8
This paper presents the development of a compact, modular rotary series elastic actuator (SEA) design that can be customized to meet the requirements of a wide range of applications. The concept incorporates flat brushless motors and planetary gearhe
Publikováno v:
2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids).
We present the UMass uBot concept for dexterous mobile manipulation. The uBot concept is built around Bernstein's definition of dexterity—“the ability to solve a motor problem correctly, quickly, rationally, and resourcefully” [1]. We contend t