Zobrazeno 1 - 10
of 411
pro vyhledávání: '"Nandi, G."'
In the modern era of Deep Learning, network parameters play a vital role in models efficiency but it has its own limitations like extensive computations and memory requirements, which may not be suitable for real time intelligent robot grasping tasks
Externí odkaz:
http://arxiv.org/abs/2308.11590
6D object pose estimation has been a research topic in the field of computer vision and robotics. Many modern world applications like robot grasping, manipulation, autonomous navigation etc, require the correct pose of objects present in a scene to p
Externí odkaz:
http://arxiv.org/abs/2212.05560
Publikováno v:
Journal of the Mechanical Behavior of Materials, Vol 17, Iss 3, Pp 149-192 (2006)
Externí odkaz:
https://doaj.org/article/231f7987bd874845a1a12f2721fc81ea
Intelligent robot grasping is a very challenging task due to its inherent complexity and non availability of sufficient labelled data. Since making suitable labelled data available for effective training for any deep learning based model including de
Externí odkaz:
http://arxiv.org/abs/2202.09821
Grasping objects intelligently is a challenging task even for humans and we spend a considerable amount of time during our childhood to learn how to grasp objects correctly. In the case of robots, we can not afford to spend that much time on making i
Externí odkaz:
http://arxiv.org/abs/2112.03001
Human Motion Prediction is a crucial task in computer vision and robotics. It has versatile application potentials such as in the area of human-robot interactions, human action tracking for airport security systems, autonomous car navigation, compute
Externí odkaz:
http://arxiv.org/abs/2108.04001
Our way of grasping objects is challenging for efficient, intelligent and optimal grasp by COBOTs. To streamline the process, here we use deep learning techniques to help robots learn to generate and execute appropriate grasps quickly. We developed a
Externí odkaz:
http://arxiv.org/abs/2107.07452
In this research article, we have reported periodic cellular automata rules for different gait state prediction and classification of the gait data using extreme machine Leaning (ELM). This research is the first attempt to use cellular automaton to u
Externí odkaz:
http://arxiv.org/abs/2105.03799
For a robot to perform complex manipulation tasks, it is necessary for it to have a good grasping ability. However, vision based robotic grasp detection is hindered by the unavailability of sufficient labelled data. Furthermore, the application of se
Externí odkaz:
http://arxiv.org/abs/2001.08477
Intelligent Object manipulation for grasping is a challenging problem for robots. Unlike robots, humans almost immediately know how to manipulate objects for grasping due to learning over the years. A grown woman can grasp objects more skilfully than
Externí odkaz:
http://arxiv.org/abs/2001.05443