Zobrazeno 1 - 10
of 198
pro vyhledávání: '"SHI Yongliang"'
Publikováno v:
Fenmo yejin jishu, Vol 42, Iss 4, Pp 367-373 (2024)
The preparation, microstructure, and mechanical properties of the Ti6Al4V titanium alloy scaffolds by extrusion molding 3D printing were systematically investigated by universal testing machine and scanning electron microscope in this paper. The prep
Externí odkaz:
https://doaj.org/article/98fa6a0240ed4ef9809875e7d08b2f01
Autor:
Zhang, Saining, Ye, Baijun, Chen, Xiaoxue, Chen, Yuantao, Zhang, Zongzheng, Peng, Cheng, Shi, Yongliang, Zhao, Hao
Robust and realistic rendering for large-scale road scenes is essential in autonomous driving simulation. Recently, 3D Gaussian Splatting (3D-GS) has made groundbreaking progress in neural rendering, but the general fidelity of large-scale road scene
Externí odkaz:
http://arxiv.org/abs/2408.15242
Autor:
Lou, Haozhe, Liu, Yurong, Pan, Yike, Geng, Yiran, Chen, Jianteng, Ma, Wenlong, Li, Chenglong, Wang, Lin, Feng, Hengzhen, Shi, Lu, Luo, Liyi, Shi, Yongliang
Real2Sim2Real plays a critical role in robotic arm control and reinforcement learning, yet bridging this gap remains a significant challenge due to the complex physical properties of robots and the objects they manipulate. Existing methods lack a com
Externí odkaz:
http://arxiv.org/abs/2408.14873
Autor:
Xu, Shiyao, Liu, Caiyun, Chen, Yuantao, Zhu, Zhenxin, Yan, Zike, Shi, Yongliang, Zhao, Hao, Zhou, Guyue
Camera relocalization is a crucial problem in computer vision and robotics. Recent advancements in neural radiance fields (NeRFs) have shown promise in synthesizing photo-realistic images. Several works have utilized NeRFs for refining camera poses,
Externí odkaz:
http://arxiv.org/abs/2405.14824
Autor:
Ye, Baijun, Liu, Caiyun, Ye, Xiaoyu, Chen, Yuantao, Wang, Yuhai, Yan, Zike, Shi, Yongliang, Zhao, Hao, Zhou, Guyue
Due to the limited model capacity, leveraging distributed Neural Radiance Fields (NeRFs) for modeling extensive urban environments has become a necessity. However, current distributed NeRF registration approaches encounter aliasing artifacts, arising
Externí odkaz:
http://arxiv.org/abs/2405.02880
The detection of traversable regions on staircases and the physical modeling constitutes pivotal aspects of the mobility of legged robots. This paper presents an onboard framework tailored to the detection of traversable regions and the modeling of p
Externí odkaz:
http://arxiv.org/abs/2405.01918
Autor:
Feng, Yixiao, Jiang, Zhou, Shi, Yongliang, Feng, Yunlong, Chen, Xiangyu, Zhao, Hao, Zhou, Guyue
Accurate localization is an essential technology for the flexible navigation of robots in large-scale environments. Both SLAM-based and map-based localization will increase the computing load due to the increase in map size, which will affect downstr
Externí odkaz:
http://arxiv.org/abs/2404.18192
Autor:
Zhao, Qingrui, Li, Mingyuan, Shi, Yongliang, Chen, Xuechao, Yu, Zhangguo, Han, Lianqiang, Fu, Zhenyuan, Zhang, Jintao, Li, Chao, Zhang, Yuanxi, Huang, Qiang
High-frequency and accurate state estimation is crucial for biped robots. This paper presents a tightly-coupled LiDAR-Inertial-Kinematic Odometry (LIKO) for biped robot state estimation based on an iterated extended Kalman filter. Beyond state estima
Externí odkaz:
http://arxiv.org/abs/2404.18047
Autor:
Jiang, Zhou, Zhu, Zhenxin, Li, Pengfei, Gao, Huan-ang, Yuan, Tianyuan, Shi, Yongliang, Zhao, Hang, Zhao, Hao
Autonomous vehicles are gradually entering city roads today, with the help of high-definition maps (HDMaps). However, the reliance on HDMaps prevents autonomous vehicles from stepping into regions without this expensive digital infrastructure. This f
Externí odkaz:
http://arxiv.org/abs/2403.10521
Autor:
Wu, Zirui, Liu, Tianyu, Luo, Liyi, Zhong, Zhide, Chen, Jianteng, Xiao, Hongmin, Hou, Chao, Lou, Haozhe, Chen, Yuantao, Yang, Runyi, Huang, Yuxin, Ye, Xiaoyu, Yan, Zike, Shi, Yongliang, Liao, Yiyi, Zhao, Hao
Nowadays, autonomous cars can drive smoothly in ordinary cases, and it is widely recognized that realistic sensor simulation will play a critical role in solving remaining corner cases by simulating them. To this end, we propose an autonomous driving
Externí odkaz:
http://arxiv.org/abs/2307.15058