Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Zheng, Chunran"'
Autor:
Liu, Zheng, Li, Haotian, Yuan, Chongjian, Liu, Xiyuan, Lin, Jiarong, Li, Rundong, Zheng, Chunran, Zhou, Bingyang, Liu, Wenyi, Zhang, Fu
In this work, we present Voxel-SLAM: a complete, accurate, and versatile LiDAR-inertial SLAM system that fully utilizes short-term, mid-term, long-term, and multi-map data associations to achieve real-time estimation and high precision mapping. The s
Externí odkaz:
http://arxiv.org/abs/2410.08935
This paper presents a unified surface reconstruction and rendering framework for LiDAR-visual systems, integrating Neural Radiance Fields (NeRF) and Neural Distance Fields (NDF) to recover both appearance and structural information from posed images
Externí odkaz:
http://arxiv.org/abs/2409.05310
This paper presents MFCalib, an innovative extrinsic calibration technique for LiDAR and RGB camera that operates automatically in targetless environments with a single data capture. At the heart of this method is using a rich set of edge information
Externí odkaz:
http://arxiv.org/abs/2409.00992
Autor:
Zheng, Chunran, Xu, Wei, Zou, Zuhao, Hua, Tong, Yuan, Chongjian, He, Dongjiao, Zhou, Bingyang, Liu, Zheng, Lin, Jiarong, Zhu, Fangcheng, Ren, Yunfan, Wang, Rong, Meng, Fanle, Zhang, Fu
This paper proposes FAST-LIVO2: a fast, direct LiDAR-inertial-visual odometry framework to achieve accurate and robust state estimation in SLAM tasks and provide great potential in real-time, onboard robotic applications. FAST-LIVO2 fuses the IMU, Li
Externí odkaz:
http://arxiv.org/abs/2408.14035
We introduce an integrated precise LiDAR, Inertial, and Visual (LIV) multimodal sensor fused mapping system that builds on the differentiable \pre{surface splatting }\now{Gaussians} to improve the mapping fidelity, quality, and structural accuracy. N
Externí odkaz:
http://arxiv.org/abs/2401.14857
To achieve accurate and robust pose estimation in Simultaneous Localization and Mapping (SLAM) task, multi-sensor fusion is proven to be an effective solution and thus provides great potential in robotic applications. This paper proposes FAST-LIVO, a
Externí odkaz:
http://arxiv.org/abs/2203.00893
In this letter, we propose a robust, real-time tightly-coupled multi-sensor fusion framework, which fuses measurement from LiDAR, inertial sensor, and visual camera to achieve robust and accurate state estimation. Our proposed framework is composed o
Externí odkaz:
http://arxiv.org/abs/2102.12400
Combining lidar in camera-based simultaneous localization and mapping (SLAM) is an effective method in improving overall accuracy, especially at a large scale outdoor scenario. Recent development of low-cost lidars (e.g. Livox lidar) enable us to exp
Externí odkaz:
http://arxiv.org/abs/2011.11357
Autor:
Li, Haotian, Zou, Yuying, Chen, Nan, Lin, Jiarong, Liu, Xiyuan, Xu, Wei, Zheng, Chunran, Li, Rundong, He, Dongjiao, Kong, Fanze, Cai, Yixi, Liu, Zheng, Zhou, Shunbo, Xue, Kaiwen, Zhang, Fu
Publikováno v:
International Journal of Robotics Research; Jul2024, Vol. 43 Issue 8, p1114-1127, 14p
Akademický článek
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