Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Qian, Jingxing"'
Autonomous robots navigating in changing environments demand adaptive navigation strategies for safe long-term operation. While many modern control paradigms offer theoretical guarantees, they often assume known extrinsic safety constraints, overlook
Externí odkaz:
http://arxiv.org/abs/2404.14546
3D object-level mapping is a fundamental problem in robotics, which is especially challenging when object CAD models are unavailable during inference. In this work, we propose a framework that can reconstruct high-quality object-level maps for unknow
Externí odkaz:
http://arxiv.org/abs/2309.09118
Autor:
Qian, Jingxing, Chatrath, Veronica, Servos, James, Mavrinac, Aaron, Burgard, Wolfram, Waslander, Steven L., Schoellig, Angela P.
Simultaneous localization and mapping (SLAM) in slowly varying scenes is important for long-term robot task completion. Failing to detect scene changes may lead to inaccurate maps and, ultimately, lost robots. Classical SLAM algorithms assume static
Externí odkaz:
http://arxiv.org/abs/2307.00488
Autor:
Qian, Jingxing, Chatrath, Veronica, Yang, Jun, Servos, James, Schoellig, Angela P., Waslander, Steven L.
Maintaining an up-to-date map to reflect recent changes in the scene is very important, particularly in situations involving repeated traversals by a robot operating in an environment over an extended period. Undetected changes may cause a deteriorat
Externí odkaz:
http://arxiv.org/abs/2205.01202
Autor:
Burnett, Keenan, Yoon, David J., Wu, Yuchen, Li, Andrew Zou, Zhang, Haowei, Lu, Shichen, Qian, Jingxing, Tseng, Wei-Kang, Lambert, Andrew, Leung, Keith Y. K., Schoellig, Angela P., Barfoot, Timothy D.
The Boreas dataset was collected by driving a repeated route over the course of one year, resulting in stark seasonal variations and adverse weather conditions such as rain and falling snow. In total, the Boreas dataset includes over 350km of driving
Externí odkaz:
http://arxiv.org/abs/2203.10168
Autor:
Burnett, Keenan, Qian, Jingxing, Du, Xintong, Liu, Linqiao, Yoon, David J., Shen, Tianchang, Sun, Susan, Samavi, Sepehr, Sorocky, Michael J., Bianchi, Mollie, Zhang, Kaicheng, Arkhangorodsky, Arkady, Sykora, Quinlan, Lu, Shichen, Huang, Yizhou, Schoellig, Angela P., Barfoot, Timothy D.
The SAE AutoDrive Challenge is a three-year collegiate competition to develop a self-driving car by 2020. The second year of the competition was held in June 2019 at MCity, a mock town built for self-driving car testing at the University of Michigan.
Externí odkaz:
http://arxiv.org/abs/2004.08752
Autor:
Li, Qiyang, Qian, Jingxing, Zhu, Zining, Bao, Xuchan, Helwa, Mohamed K., Schoellig, Angela P.
Trajectory tracking control for quadrotors is important for applications ranging from surveying and inspection, to film making. However, designing and tuning classical controllers, such as proportional-integral-derivative (PID) controllers, to achiev
Externí odkaz:
http://arxiv.org/abs/1610.06283
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Akademický článek
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Publikováno v:
Proceedings of China Modern Logistics Engineering; 2015, p347-358, 12p