Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Nitin J. Sanket"'
Publikováno v:
Electronics Letters, Vol 57, Iss 16, Pp 614-617 (2021)
Abstract Global optical flow estimation is the foundation stone for obtaining odometry which is used to enable aerial robot navigation. However, such a method has to be of low latency and high robustness whilst also respecting the size, weight, area
Externí odkaz:
https://doaj.org/article/51bc84a3de91420f92c3f1ac8725a706
Autor:
Kanishka Ganguly, Pavan Mantripragada, Chethan M. Parameshwara, Cornelia Fermüller, Nitin J. Sanket, Yiannis Aloimonos
Publikováno v:
Frontiers in Robotics and AI, Vol 9 (2022)
Tactile sensing for robotics is achieved through a variety of mechanisms, including magnetic, optical-tactile, and conductive fluid. Currently, the fluid-based sensors have struck the right balance of anthropomorphic sizes and shapes and accuracy of
Externí odkaz:
https://doaj.org/article/071630e0008641888e26ffb8a6aa7389
Publikováno v:
Electronics Letters, Vol 57, Iss 16, Pp 614-617 (2021)
Global optical flow estimation is the foundation stone for obtaining odometry which is used to enable aerial robot navigation. However, such a method has to be of low latency and high robustness whilst also respecting the size, weight, area and power
Publikováno v:
ICRA
Morphable design and depth-based visual control are two upcoming trends leading to advancements in the field of quadrotor autonomy. Stereo-cameras have struck the perfect balance of weight and accuracy of depth estimation but suffer from the problem
Autor:
Chethan M. Parameshwara, Simin Li, Cornelia Fermuller, Nitin J. Sanket, Matthew S. Evanusa, Yiannis Aloimonos
Spiking Neural Networks (SNN) are the so-called third generation of neural networks which attempt to more closely match the functioning of the biological brain. They inherently encode temporal data, allowing for training with less energy usage and ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fd75f3dc661df96948a8deebbfbcdd64
Autor:
Cornelia Fermüller, Nitin J. Sanket, Chethan M. Parameshwara, Chahat Deep Singh, Yiannis Aloimonos
Publikováno v:
ICRA
Segmentation of moving objects in dynamic scenes is a key process in scene understanding for navigation tasks. Classical cameras suffer from motion blur in such scenarios rendering them effete. On the contrary, event cameras, because of their high te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23f43ea22b010699f15d674f74e66a2b
Autor:
Nitin J. Sanket, Yiannis Aloimonos, Chahat Deep Singh, Cornelia Fermüller, Ashwin V. Kuruttukulam, Davide Scaramuzza, Chethan M. Parameshwara
Publikováno v:
ICRA
Dynamic obstacle avoidance on quadrotors requires low latency. A class of sensors that are particularly suitable for such scenarios are event cameras. In this paper, we present a deep learning -- based solution for dodging multiple dynamic obstacles
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa02fac63813c74f43776135ac312017
Although quadrotors, and aerial robots in general, are inherently active agents, their perceptual capabilities in literature so far have been mostly passive in nature. Researchers and practitioners today use traditional computer vision algorithms wit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89ce9023ac5f53fd1f928701287bb508
Although cluttered indoor scenes have a lot of useful high-level semantic information which can be used for mapping and localization, most visual odometry (VO) algorithms rely on the usage of geometric features such as points, lines, and planes. Late
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7305a0e2ed79b293267250a96d43f3fb
Publikováno v:
ICRA
We present PennCOSYVIO, a new challenging Visual Inertial Odometry (VIO) benchmark with synchronized data from a VI-sensor (stereo camera and IMU), two Project Tango hand-held devices, and three GoPro Hero 4 cameras. Recorded at UPenn's Singh center,