Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Xieyuanli Chen"'
Publikováno v:
IEEE Robotics and Automation Letters. 6:2060-2067
Many modern robotics applications rely on 3D maps of the environment. Due to the large memory requirements of dense 3D maps, compression techniques are often necessary to store or transmit 3D maps efficiently. In this work, we investigate the problem
Autor:
Kaihong Huang, Chenghao Shi, Xieyuanli Chen, Hui Zhang, Ruibin Guo, Wenbang Deng, Zhiqian Zhou
Publikováno v:
IEEE Access, Vol 8, Pp 221320-221329 (2020)
In this paper, we propose a semantic simultaneous localization and mapping (SLAM) framework for rescue robots, and report its use in navigation tasks. Our framework can generate not only geometric maps in the form of dense point-clouds but also corre
Publikováno v:
ICIA
Remarkable performance has been achieved using the state-of-the-art monocular Simultaneous Localization and Mapping (SLAM) algorithms. However, due to the scale ambiguity limitation of monocular vision, the existing monocular SLAM systems can not dir
Publikováno v:
2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER).
In this paper, we propose a distributed multi-robot SLAM system, where each robot estimates its pose and reconstructs the environment simultaneously using the same monocular SLAM algorithm, while sharing the results of their incremental maps by strea
Publikováno v:
International Journal of Advanced Robotic Systems, Vol 15 (2018)
BASE-Bielefeld Academic Search Engine
BASE-Bielefeld Academic Search Engine
In this article, we propose a distributed and collaborative monocular simultaneous localization and mapping system for the multi-robot system in large-scale environments, where monocular vision is the only exteroceptive sensor. Each robot estimates i
Publikováno v:
SSRR
In this paper, we propose a monocular SLAM system for robotic urban search and rescue (USAR), based on which most USAR tasks (e.g. localization, mapping, exploration and object recognition) can be fulfilled by rescue robots with only a single camera.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319683447
ICVS
ICVS
Remarkable performance has been achieved using the state-of-the-art monocular Simultaneous Localization and Mapping (SLAM) algorithms. However, tracking failure is still a challenging problem during the monocular SLAM process, and it seems to be even
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1aec452f96ec6b9c4e83a9771e183a2
https://doi.org/10.1007/978-3-319-68345-4_12
https://doi.org/10.1007/978-3-319-68345-4_12