Zobrazeno 1 - 10
of 291
pro vyhledávání: '"ZHU Yilong"'
The stability of visual odometry (VO) systems is undermined by degraded image quality, especially in environments with significant illumination changes. This study employs a deep reinforcement learning (DRL) framework to train agents for exposure con
Externí odkaz:
http://arxiv.org/abs/2408.17005
Autor:
Wei, Hexiang, Jiao, Jianhao, Hu, Xiangcheng, Yu, Jingwen, Xie, Xupeng, Wu, Jin, Zhu, Yilong, Liu, Yuxuan, Wang, Lujia, Liu, Ming
Simultaneous Localization and Mapping (SLAM) technology has been widely applied in various robotic scenarios, from rescue operations to autonomous driving. However, the generalization of SLAM algorithms remains a significant challenge, as current dat
Externí odkaz:
http://arxiv.org/abs/2404.08563
Autor:
Jiao, Jianhao, Wei, Hexiang, Hu, Tianshuai, Hu, Xiangcheng, Zhu, Yilong, He, Zhijian, Wu, Jin, Yu, Jingwen, Xie, Xupeng, Huang, Huaiyang, Geng, Ruoyu, Wang, Lujia, Liu, Ming
Combining multiple sensors enables a robot to maximize its perceptual awareness of environments and enhance its robustness to external disturbance, crucial to robotic navigation. This paper proposes the FusionPortable benchmark, a complete multi-sens
Externí odkaz:
http://arxiv.org/abs/2208.11865
This paper investigates two typical image-type representations for event camera-based tracking: time surface (TS) and event map (EM). Based on the original TS-based tracker, we make use of these two representations' complementary strengths to develop
Externí odkaz:
http://arxiv.org/abs/2104.09887
Autor:
Jiao, Jianhao, Zhu, Yilong, Ye, Haoyang, Huang, Huaiyang, Yun, Peng, Jiang, Linxin, Wang, Lujia, Liu, Ming
Modern LiDAR-SLAM (L-SLAM) systems have shown excellent results in large-scale, real-world scenarios. However, they commonly have a high latency due to the expensive data association and nonlinear optimization. This paper demonstrates that actively s
Externí odkaz:
http://arxiv.org/abs/2103.13090
Combining multiple LiDARs enables a robot to maximize its perceptual awareness of environments and obtain sufficient measurements, which is promising for simultaneous localization and mapping (SLAM). This paper proposes a system to achieve robust and
Externí odkaz:
http://arxiv.org/abs/2010.14294
Autor:
Liu, Tianyu, Liao, Qinghai, Gan, Lu, Ma, Fulong, Cheng, Jie, Xie, Xupeng, Wang, Zhe, Chen, Yingbing, Zhu, Yilong, Zhang, Shuyang, Chen, Zhengyong, Liu, Yang, Xie, Meng, Yu, Yang, Guo, Zitong, Li, Guang, Yuan, Peidong, Han, Dong, Chen, Yuying, Ye, Haoyang, Jiao, Jianhao, Yun, Peng, Xu, Zhenhua, Wang, Hengli, Huang, Huaiyang, Wang, Sukai, Cai, Peide, Sun, Yuxiang, Liu, Yandong, Wang, Lujia, Liu, Ming
Publikováno v:
IEEE Robotics and Automation Magazine, 2021
Since early 2020, the coronavirus disease 2019 (COVID-19) has spread rapidly across the world. As at the date of writing this article, the disease has been globally reported in 223 countries and regions, infected over 108 million people and caused ov
Externí odkaz:
http://arxiv.org/abs/2004.07480
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Akademický článek
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Road curb detection is very important and necessary for autonomous driving because it can improve the safety and robustness of robot navigation in the outdoor environment. In this paper, a novel road curb detection method based on tensor voting is pr
Externí odkaz:
http://arxiv.org/abs/1911.12937