Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Xieyuanli Chen"'
Autor:
Jingtao Sun, Yaonan Wang, Mingtao Feng, Danwei Wang, Jiawen Zhao, Cyrill Stachniss, Xieyuanli Chen
Publikováno v:
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Publikováno v:
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
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:
2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Publikováno v:
ECMR
European Conference on Mobile Robots (ECMR)
2021 European Conference on Mobile Robots (ECMR)
European Conference on Mobile Robots (ECMR)
2021 European Conference on Mobile Robots (ECMR)
Reliable and accurate localization is crucial for mobile autonomous systems. Pole-like objects, such as traffic signs, poles, lamps, etc., are ideal landmarks for localization in urban environments due to their local distinctiveness and long-term sta
Autor:
Chenghao Shi, Hui Zhang, Ruibin Guo, Zhiqian Zhou, Wenbang Deng, Xieyuanli Chen, Kaihong Huang
Publikováno v:
2020 Chinese Automation Congress (CAC).
Semantic information has proven to be an enabling factor for robots to better understand their surroundings. In this paper, we propose an RGB-D based semantic simultaneous localization and mapping (SLAM) framework for rescue robots. By augmenting the
Autor:
Emanuele Palazzolo, Cyrill Stachniss, Xieyuanli Chen, Andres Milioto, Philippe Giguère, Jens Behley
Publikováno v:
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Reliable and accurate localization and mapping are key components of most autonomous systems. Besides geometric information about the mapped environment, the semantics plays an important role to enable intelligent navigation behaviors. In most realis
Publikováno v:
ICIA
Basic abilities for robots in rescue environments consisted of autonomous exploration and target recognition. In this essay, we combine these two abilities and propose a target-based robot autonomous exploration method. When no victim is found, robot
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