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of 3 290
pro vyhledávání: '"Mohammadi, Ali"'
Cycling as an active mode of transport is increasing across all Europe [1]. Multiple benefits are coming from cycling both for the single user and the society as a whole. With increasing cycling, we expect more conflicts to happen between cyclists an
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82462
https://tud.qucosa.de/api/qucosa%3A82462/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82462/attachment/ATT-0/
Autor:
Ginting, Muhammad Fadhil, Kim, Sung-Kyun, Fan, David D., Palieri, Matteo, Kochenderfer, Mykel J., Agha-Mohammadi, Ali-akbar
This paper addresses the problem of object-goal navigation in autonomous inspections in real-world environments. Object-goal navigation is crucial to enable effective inspections in various settings, often requiring the robot to identify the target o
Externí odkaz:
http://arxiv.org/abs/2405.09822
Autor:
Tilwani, Deepa, Saxena, Yash, Mohammadi, Ali, Raff, Edward, Sheth, Amit, Parthasarathy, Srinivasan, Gaur, Manas
Automatic citation generation for sentences in a document or report is paramount for intelligence analysts, cybersecurity, news agencies, and education personnel. In this research, we investigate whether large language models (LLMs) are capable of ge
Externí odkaz:
http://arxiv.org/abs/2405.02228
Autor:
Stathoulopoulos, Nikolaos, Lindqvist, Björn, Koval, Anton, Agha-mohammadi, Ali-akbar, Nikolakopoulos, George
In this article, a novel approach for merging 3D point cloud maps in the context of egocentric multi-robot exploration is presented. Unlike traditional methods, the proposed approach leverages state-of-the-art place recognition and learned descriptor
Externí odkaz:
http://arxiv.org/abs/2404.18006
Autor:
Vlahov, Bogdan, Gibson, Jason, Fan, David D., Spieler, Patrick, Agha-mohammadi, Ali-akbar, Theodorou, Evangelos A.
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 5, pp.4543-4550, 2024
Sampling-based model-predictive controllers have become a powerful optimization tool for planning and control problems in various challenging environments. In this paper, we show how the default choice of uncorrelated Gaussian distributions can be im
Externí odkaz:
http://arxiv.org/abs/2404.03094
This study investigates learning from demonstration (LfD) for contact-rich tasks. The procedure for choosing a task frame to express the learned signals for the motion and interaction wrench is often omitted or using expert insight. This article pres
Externí odkaz:
http://arxiv.org/abs/2404.01900
A staircase localization method is proposed for robots to explore urban environments autonomously. The proposed method employs a modular design in the form of a cascade pipeline consisting of three modules of stair detection, line segment detection,
Externí odkaz:
http://arxiv.org/abs/2403.17330
Autor:
Ginting, Muhammad Fadhil, Fan, David D., Kim, Sung-Kyun, Kochenderfer, Mykel J., Agha-mohammadi, Ali-akbar
This paper addresses the problem of autonomous robotic inspection in complex and unknown environments. This capability is crucial for efficient and precise inspections in various real-world scenarios, even when faced with perceptual uncertainty and l
Externí odkaz:
http://arxiv.org/abs/2401.17191
Autor:
Mohammadi, Mohammad, Mohammadi, Ali
This study delves into the shift from centralized to decentralized approaches in the electricity industry, with a particular focus on how machine learning (ML) advancements play a crucial role in empowering renewable energy sources and improving grid
Externí odkaz:
http://arxiv.org/abs/2310.15468
We estimate the frequency of singular matrices and of matrices of a given rank whose entries are parametrised by arbitrary polynomials over the integers and modulo a prime $p$. In particular, in the integer case, we improve a recent bound of V. Blome
Externí odkaz:
http://arxiv.org/abs/2310.05038