Zobrazeno 1 - 10
of 116
pro vyhledávání: '"Ryan M. Eustice"'
Autor:
Xi Lin, Yewei Huang, Dingyi Sun, Tzu-Yuan Lin, Brendan Englot, Ryan M. Eustice, Maani Ghaffari
Publikováno v:
IEEE Access, Vol 11, Pp 97239-97249 (2023)
The accuracy of RGB-D SLAM systems is sensitive to the image quality, and can be significantly compromised in adverse situations such as when input images are blurry, lacking in texture features, or overexposed. In this paper, based on Continuous Dir
Externí odkaz:
https://doaj.org/article/7c0263c04d7a4fdbbeda0edd869df7cf
Autor:
Lu Gan, Youngji Kim, Jessy W. Grizzle, Jeffrey M. Walls, Ayoung Kim, Ryan M. Eustice, Maani Ghaffari
Publikováno v:
IEEE Transactions on Robotics. 39:699-717
This article presents a novel and flexible multitask multilayer Bayesian mapping framework with readily extendable attribute layers. The proposed framework goes beyond modern metric-semantic maps to provide even richer environmental information for r
Publikováno v:
IEEE Robotics and Automation Letters. 4:4563-4570
The essence of most shape registration algorithms is to find correspondences between two point clouds and then to solve for a rigid body transformation that aligns the geometry. The main drawback is that the point clouds are obtained by placing the s
Autor:
Ryan M. Eustice
Publikováno v:
SPIE Future Sensing Technologies.
Publikováno v:
ICRA
Determining the rigid-body transformation be-tween 2D image data and 3D point cloud data has applications for mobile robotics including sensor calibration and localizing into a prior map. Common approaches to 2D-3D registration use least-squares solv
Publikováno v:
IROS
WiFi technology has been used pervasively in fine-grained indoor localization, gesture recognition, and adaptive communication. Achieving better performance in these tasks generally boils down to differentiating Line-Of-Sight (LOS) from Non-Line-Of-S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31ac2d9764ce7d2769a9ac91983afd65
http://arxiv.org/abs/2002.00484
http://arxiv.org/abs/2002.00484
Autor:
Ray Zhang, Maani Ghaffari, Jessy W. Grizzle, Tzu-Yuan Lin, Ryan M. Eustice, Chien Erh Lin, William Clark, Steven A. Parkison
Publikováno v:
ICRA
This paper reports on a novel nonparametric rigid point cloud registration framework that jointly integrates geometric and semantic measurements such as color or semantic labels into the alignment process and does not require explicit data associatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6629a3fbb56a4e58f1ecdf33b549ea1c
Autor:
Zhong Cao, Pingping Lu, Maani Ghaffari, Ryan M. Eustice, Yuanxin Zhong, Minghan Zhu, Huei Peng
Publikováno v:
IROS
This paper reports a new continuous 3D loss function for learning depth from monocular images. The dense depth prediction from a monocular image is supervised using sparse LIDAR points, which enables us to leverage available open source datasets with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::faa3becef1819c9e8beb83523c87991c
Publikováno v:
IEEE Robotics and Automation Letters. 3:2330-2337
This letter reports on a real-time simultaneous localization and mapping (SLAM) algorithm for an underwater robot using an imaging forward-looking sonar and its application in the area of autonomous underwater ship hull inspection. The proposed algor
Autor:
Ryan M. Eustice, Ryan W. Wolcott
Publikováno v:
The International Journal of Robotics Research. 36:292-319
This paper reports on a fast multiresolution scan matcher for local vehicle localization of self-driving cars. State-of-the-art approaches to vehicle localization rely on observing road surface reflectivity with a 3D light detection and ranging (LIDA