Zobrazeno 1 - 10
of 265
pro vyhledávání: '"Banerjee, Ashis"'
Autor:
Samani, Ekta U., Banerjee, Ashis G.
Visual object recognition in unseen and cluttered indoor environments is a challenging problem for mobile robots. This study presents a 3D shape and color-based descriptor, TOPS2, for point clouds generated from RGB-D images and an accompanying recog
Externí odkaz:
http://arxiv.org/abs/2408.01579
As robotics and augmented reality applications increasingly rely on precise and efficient 6D object pose estimation, real-time performance on edge devices is required for more interactive and responsive systems. Our proposed Sparse Color-Code Net (SC
Externí odkaz:
http://arxiv.org/abs/2406.02977
Holographic Optical Tweezers (HOT) are powerful tools that can manipulate micro and nano-scale objects with high accuracy and precision. They are most commonly used for biological applications, such as cellular studies, and more recently, micro-struc
Externí odkaz:
http://arxiv.org/abs/2404.17045
Autor:
Krishnan, Anand, Yang, Xingjian, Seth, Utsav, Jeyachandran, Jonathan M., Ahn, Jonathan Y., Gardner, Richard, Pedigo, Samuel F., Adriana, Blom-Schieber, Banerjee, Ashis G., Manohar, Krithika
Hand-intensive manufacturing processes, such as composite layup and textile draping, require significant human dexterity to accommodate task complexity. These strenuous hand motions often lead to musculoskeletal disorders and rehabilitation surgeries
Externí odkaz:
http://arxiv.org/abs/2403.05591
We provide the first step toward developing a hierarchical control-estimation framework to actively plan robot trajectories for anomaly detection in confined spaces. The space is represented globally using a directed region graph, where a region is a
Externí odkaz:
http://arxiv.org/abs/2310.00588
Autor:
Samani, Ekta U., Banerjee, Ashis G.
Visual object recognition in unseen and cluttered indoor environments is a challenging problem for mobile robots. Toward this goal, we extend our previous work to propose the TOPS2 descriptor, and an accompanying recognition framework, THOR2, inspire
Externí odkaz:
http://arxiv.org/abs/2309.08239
Time series forecasting has received a lot of attention, with recurrent neural networks (RNNs) being one of the widely used models due to their ability to handle sequential data. Previous studies on RNN time series forecasting, however, show inconsis
Externí odkaz:
http://arxiv.org/abs/2307.15830