Zobrazeno 1 - 10
of 160
pro vyhledávání: '"Cai, Xiaoyi"'
Autor:
Cai, Xiaoyi, Queeney, James, Xu, Tong, Datar, Aniket, Pan, Chenhui, Miller, Max, Flather, Ashton, Osteen, Philip R., Roy, Nicholas, Xiao, Xuesu, How, Jonathan P.
Self-supervised learning is a powerful approach for developing traversability models for off-road navigation, but these models often struggle with inputs unseen during training. Existing methods utilize techniques like evidential deep learning to qua
Externí odkaz:
http://arxiv.org/abs/2409.03005
Autor:
Kondo, Kota, Tagliabue, Andrea, Cai, Xiaoyi, Tewari, Claudius, Garcia, Olivia, Espitia-Alvarez, Marcos, How, Jonathan P.
Traditional optimization-based planners, while effective, suffer from high computational costs, resulting in slow trajectory generation. A successful strategy to reduce computation time involves using Imitation Learning (IL) to develop fast neural ne
Externí odkaz:
http://arxiv.org/abs/2405.01758
Autor:
Cai, Xiaoyi, Ancha, Siddharth, Sharma, Lakshay, Osteen, Philip R., Bucher, Bernadette, Phillips, Stephen, Wang, Jiuguang, Everett, Michael, Roy, Nicholas, How, Jonathan P.
Traversing terrain with good traction is crucial for achieving fast off-road navigation. Instead of manually designing costs based on terrain features, existing methods learn terrain properties directly from data via self-supervision to automatically
Externí odkaz:
http://arxiv.org/abs/2311.06234
Autor:
Sharma, Lakshay, Everett, Michael, Lee, Donggun, Cai, Xiaoyi, Osteen, Philip, How, Jonathan P.
A key challenge in fast ground robot navigation in 3D terrain is balancing robot speed and safety. Recent work has shown that 2.5D maps (2D representations with additional 3D information) are ideal for real-time safe and fast planning. However, the p
Externí odkaz:
http://arxiv.org/abs/2210.06605
A key challenge in off-road navigation is that even visually similar terrains or ones from the same semantic class may have substantially different traction properties. Existing work typically assumes no wheel slip or uses the expected traction for m
Externí odkaz:
http://arxiv.org/abs/2210.00153
Autor:
Cai, Xiaoyi, Schlotfeldt, Brent, Khosoussi, Kasra, Atanasov, Nikolay, Pappas, George J., How, Jonathan P.
This paper considers the problem of safely coordinating a team of sensor-equipped robots to reduce uncertainty about a dynamical process, where the objective trades off information gain and energy cost. Optimizing this trade-off is desirable, but lea
Externí odkaz:
http://arxiv.org/abs/2208.00262
Motion planning in off-road environments requires reasoning about both the geometry and semantics of the scene (e.g., a robot may be able to drive through soft bushes but not a fallen log). In many recent works, the world is classified into a finite
Externí odkaz:
http://arxiv.org/abs/2203.13429
Publikováno v:
In Science of the Total Environment 20 October 2024 948
Publikováno v:
In International Journal of Thermal Sciences January 2025 207
Autor:
Chen, Rongxin, Cai, Xiaoyi, He, Xinyu, Zhang, Tengyi, Eldona, Calvin, Zhang, Qi, Cheng, Li, Shen, Ze Xiang
Publikováno v:
In Chemical Engineering Journal 15 May 2024 488