Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Eltouny, Kareem"'
There has been a growing utilization of industrial robots as complementary collaborators for human workers in re-manufacturing sites. Such a human-robot collaboration (HRC) aims to assist human workers in improving the flexibility and efficiency of l
Externí odkaz:
http://arxiv.org/abs/2405.09779
This paper presents a novel knowledge-informed graph neural planner (KG-Planner) to address the challenge of efficiently planning collision-free motions for robots in high-dimensional spaces, considering both static and dynamic environments involving
Externí odkaz:
http://arxiv.org/abs/2405.07962
Visual inspection is predominantly used to evaluate the state of civil structures, but recent developments in unmanned aerial vehicles (UAVs) and artificial intelligence have increased the speed, safety, and reliability of the inspection process. In
Externí odkaz:
http://arxiv.org/abs/2308.03006
Ensuring the safety of human workers in a collaborative environment with robots is of utmost importance. Although accurate pose prediction models can help prevent collisions between human workers and robots, they are still susceptible to critical err
Externí odkaz:
http://arxiv.org/abs/2307.03610
Autor:
Eltouny, Kareem1,2 (AUTHOR) kaeltouny@sgh.com, Sajedi, Seyedomid1,3 (AUTHOR) ssajedi@thorntontomasetti.com, Liang, Xiao4 (AUTHOR) xliang@tamu.edu
Publikováno v:
Sensors (14248220). Sep2024, Vol. 24 Issue 18, p6007. 19p.
Visual inspection is the predominant technique for evaluating the condition of civil infrastructure. The recent advances in unmanned aerial vehicles (UAVs) and artificial intelligence have made the visual inspections faster, safer, and more reliable.
Externí odkaz:
http://arxiv.org/abs/2210.12175
Autor:
Eltouny, Kareem, Liang, Xiao
In a world of aging infrastructure, structural health monitoring (SHM) emerges as a major step towards resilient and sustainable societies. The current advancements in machine learning and sensor technology have made SHM a more promising damage detec
Externí odkaz:
http://arxiv.org/abs/2009.13692
Akademický článek
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Autor:
Eltouny, Kareem1 (AUTHOR), Gomaa, Mohamed1 (AUTHOR), Liang, Xiao1 (AUTHOR) liangx@buffalo.edu
Publikováno v:
Sensors (14248220). Mar2023, Vol. 23 Issue 6, p3290. 40p.
Autor:
Eltouny, Kareem A.1 (AUTHOR), Liang, Xiao1 (AUTHOR) liangx@buffalo.edu
Publikováno v:
Computer-Aided Civil & Infrastructure Engineering. Feb2023, Vol. 38 Issue 3, p271-287. 17p.