Zobrazeno 1 - 10
of 38
pro vyhledávání: '"Huang, Huaiyang"'
Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrast
Externí odkaz:
http://arxiv.org/abs/2407.09091
Predicting accurate depth with monocular images is important for low-cost robotic applications and autonomous driving. This study proposes a comprehensive self-supervised framework for accurate scale-aware depth prediction on autonomous driving scene
Externí odkaz:
http://arxiv.org/abs/2304.10719
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
Autor:
Huang, Huaiyang, Sun, Yuxiang, Wu, Jin, Jiao, Jiaohao, Hu, Xiangcheng, Zheng, Linwei, Wang, Lujia, Liu, Ming
Multiview registration is used to estimate Rigid Body Transformations (RBTs) from multiple frames and reconstruct a scene with corresponding scans. Despite the success of pairwise registration and pose synchronization, the concept of Bundle Adjustmen
Externí odkaz:
http://arxiv.org/abs/2108.02976
Traditional approaches for Visual Simultaneous Localization and Mapping (VSLAM) rely on low-level vision information for state estimation, such as handcrafted local features or the image gradient. While significant progress has been made through this
Externí odkaz:
http://arxiv.org/abs/2108.02028
Autonomous car racing is a challenging task in the robotic control area. Traditional modular methods require accurate mapping, localization and planning, which makes them computationally inefficient and sensitive to environmental changes. Recently, d
Externí odkaz:
http://arxiv.org/abs/2107.08325
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
In this paper, we introduce a method for visual relocalization using the geometric information from a 3D surfel map. A visual database is first built by global indices from the 3D surfel map rendering, which provides associations between image points
Externí odkaz:
http://arxiv.org/abs/2104.03856
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
Visual Localization is an essential component in autonomous navigation. Existing approaches are either based on the visual structure from SLAM/SfM or the geometric structure from dense mapping. To take the advantages of both, in this work, we present
Externí odkaz:
http://arxiv.org/abs/2011.04173