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pro vyhledávání: '"Omama, Mohd."'
In this paper we show an effective means of integrating data driven frameworks to sampling based optimal control to vastly reduce the compute time for easy adoption and adaptation to real time applications such as on-road autonomous driving in the pr
Externí odkaz:
http://arxiv.org/abs/2310.13077
Autor:
Jatavallabhula, Krishna Murthy, Kuwajerwala, Alihusein, Gu, Qiao, Omama, Mohd, Chen, Tao, Maalouf, Alaa, Li, Shuang, Iyer, Ganesh, Saryazdi, Soroush, Keetha, Nikhil, Tewari, Ayush, Tenenbaum, Joshua B., de Melo, Celso Miguel, Krishna, Madhava, Paull, Liam, Shkurti, Florian, Torralba, Antonio
Building 3D maps of the environment is central to robot navigation, planning, and interaction with objects in a scene. Most existing approaches that integrate semantic concepts with 3D maps largely remain confined to the closed-set setting: they can
Externí odkaz:
http://arxiv.org/abs/2302.07241
Autor:
Omama, Mohd, Sriraman, Sundar Sripada Venugopalaswamy, Chinchali, Sandeep, Singh, Arun Kumar, Krishna, K. Madhava
Modern autonomous vehicles (AVs) often rely on vision, LIDAR, and even radar-based simultaneous localization and mapping (SLAM) frameworks for precise localization and navigation. However, modern SLAM frameworks often lead to unacceptably high levels
Externí odkaz:
http://arxiv.org/abs/2203.06897
We embark on a hitherto unreported problem of an autonomous robot (self-driving car) navigating in dynamic scenes in a manner that reduces its localization error and eventual cumulative drift or Absolute Trajectory Error, which is pronounced in such
Externí odkaz:
http://arxiv.org/abs/2110.14928
Fire disasters typically result in lot of loss to life and property. It is therefore imperative that precise, fast, and possibly portable solutions to detect fire be made readily available to the masses at reasonable prices. There have been several r
Externí odkaz:
http://arxiv.org/abs/1905.11922
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