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pro vyhledávání: '"Higgins, Ian"'
Autor:
Park, Jong Hoon, Chen, Lawrence, Higgins, Ian, Zheng, Zhaobo, Mehrotra, Shashank, Salubre, Kevin, Mousaei, Mohammadreza, Willits, Steven, Levedahl, Blain, Buker, Timothy, Xing, Eliot, Misu, Teruhisa, Scherer, Sebastian, Oh, Jean
Vertical take-off and landing (VTOL) aircraft do not require a prolonged runway, thus allowing them to land almost anywhere. In recent years, their flexibility has made them popular in development, research, and operation. When compared to traditiona
Externí odkaz:
http://arxiv.org/abs/2406.06448
Autor:
Patrikar, Jay, Dantas, Joao, Moon, Brady, Hamidi, Milad, Ghosh, Sourish, Keetha, Nikhil, Higgins, Ian, Chandak, Atharva, Yoneyama, Takashi, Scherer, Sebastian
We introduce TartanAviation, an open-source multi-modal dataset focused on terminal-area airspace operations. TartanAviation provides a holistic view of the airport environment by concurrently collecting image, speech, and ADS-B trajectory data using
Externí odkaz:
http://arxiv.org/abs/2403.03372
Autor:
He, Yao, Cisneros, Ivan, Keetha, Nikhil, Patrikar, Jay, Ye, Zelin, Higgins, Ian, Hu, Yaoyu, Kapoor, Parv, Scherer, Sebastian
Robust and accurate localization for Unmanned Aerial Vehicles (UAVs) is an essential capability to achieve autonomous, long-range flights. Current methods either rely heavily on GNSS, face limitations in visual-based localization due to appearance va
Externí odkaz:
http://arxiv.org/abs/2310.16299
Autor:
Navarro, Ingrid, Patrikar, Jay, Dantas, Joao P. A., Baijal, Rohan, Higgins, Ian, Scherer, Sebastian, Oh, Jean
The fast-growing demand for fully autonomous robots in shared spaces calls for the development of trustworthy agents that can safely and seamlessly navigate in crowded environments. Recent models for motion prediction show promise in characterizing s
Externí odkaz:
http://arxiv.org/abs/2309.13144
Autor:
Zhao, Shibo, Gao, Yuanjun, Wu, Tianhao, Singh, Damanpreet, Jiang, Rushan, Sun, Haoxiang, Sarawata, Mansi, Qiu, Yuheng, Whittaker, Warren, Higgins, Ian, Du, Yi, Su, Shaoshu, Xu, Can, Keller, John, Karhade, Jay, Nogueira, Lucas, Saha, Sourojit, Zhang, Ji, Wang, Wenshan, Wang, Chen, Scherer, Sebastian
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, WA, June 2024
Simultaneous localization and mapping (SLAM) is a fundamental task for numerous applications such as autonomous navigation and exploration. Despite many SLAM datasets have been released, current SLAM solutions still struggle to have sustained and res
Externí odkaz:
http://arxiv.org/abs/2307.07607
Autor:
Navarro, Ingrid, Patrikar, Jay, Dantas, Joao P. A., Baijal, Rohan, Higgins, Ian, Scherer, Sebastian, Oh, Jean
The fast-growing demand for fully autonomous aerial operations in shared spaces necessitates developing trustworthy agents that can safely and seamlessly navigate in crowded, dynamic spaces. In this work, we propose Social Robot Tree Search (SoRTS),
Externí odkaz:
http://arxiv.org/abs/2304.01428
Autor:
Patrikar, Jay, Dantas, Joao P. A., Ghosh, Sourish, Kapoor, Parv, Higgins, Ian, Aloor, Jasmine J., Navarro, Ingrid, Sun, Jimin, Stoler, Ben, Hamidi, Milad, Baijal, Rohan, Moon, Brady, Oh, Jean, Scherer, Sebastian
We propose developing an integrated system to keep autonomous unmanned aircraft safely separated and behave as expected in conjunction with manned traffic. The main goal is to achieve safe manned-unmanned vehicle teaming to improve system performance
Externí odkaz:
http://arxiv.org/abs/2211.06932
Akademický článek
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