Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Yongsheng Ou"'
Autor:
Tianyou Zhao, Lingui Yang, XiaoXian Wu, Xiaoming Gao, Ruishen Huang, Zhaochen Wang, Yongsheng Ou, Pingzhen Li, Jiong Zhang, Xiongcong Guan, Yunfeng Zhan, Xiufeng Tang, Hui Meng
Publikováno v:
Next Materials, Vol 3, Iss , Pp 100162- (2024)
Although single-atom M-N-C electrocatalysts have demonstrated their potential in metal-air batteries and fuel cells, their activity for oxygen reduction reaction (ORR) needs to be further improved. Regulating the electronic structure of M-Nx single s
Externí odkaz:
https://doaj.org/article/05275a82144f419ba63a1c08912906d6
Publikováno v:
Sensors, Vol 24, Iss 12, p 4011 (2024)
Simultaneous localization and mapping (SLAM) is a hot research area that is widely required in many robotics applications. In SLAM technology, it is essential to explore an accurate and efficient map model to represent the environment and develop the
Externí odkaz:
https://doaj.org/article/89580cd6090d4f47bb56835d61dc05a4
A self‐stabilised walking gait for humanoid robots based on the essential model with internal states
Autor:
Qiuyue Luo, Christine Chevallereau, Yongsheng Ou, Jianxin Pang, Victor De‐León‐Gómez, Yannick Aoustin
Publikováno v:
IET Cyber-systems and Robotics, Vol 4, Iss 4, Pp 283-297 (2022)
Abstract Walking stability is one of the key issues for humanoid robots. A self‐stabilised walking gait for a full dynamic model of humanoid robots is proposed. For simplified models, that is, the linear inverted pendulum model and variable‐lengt
Externí odkaz:
https://doaj.org/article/b1ff15743e5545deba370b6ec7a18822
Autor:
Ailan Situ, Tianyou Zhao, Yuetong Huang, Pingzhen Li, Lingui Yang, Zehong Zhang, Zhaochen Wang, Yongsheng Ou, Xiongcong Guan, Jinxiu Wen, Jiong Zhang, Yunfeng Zhan, Xiufeng Tang
Publikováno v:
Catalysts, Vol 13, Iss 8, p 1161 (2023)
The development of efficient non-precious metal electrocatalysts for oxygen reduction reaction (ORR) to replace Pt-based methods is crucial for the applications of fuel cells and metal–air batteries. In this study, a bimetallic M-N-C catalyst with
Externí odkaz:
https://doaj.org/article/6efd01294dd64f75a456ba278943b472
Publikováno v:
IET Intelligent Transport Systems, Vol 14, Iss 5, Pp 278-287 (2020)
A fast‐running human detection system for the unmanned aerial vehicle (UAV) based on optical flow and deep convolution networks is proposed in this study. In the system, running humans can be detected in real‐time at the speed of 15 frames per se
Externí odkaz:
https://doaj.org/article/53219e9955a84ccb9f99523024193909
Publikováno v:
Sensors, Vol 23, Iss 2, p 813 (2023)
Recently, person-following robots have been increasingly used in many real-world applications, and they require robust and accurate person identification for tracking. Recent works proposed to use re-identification metrics for identification of the t
Externí odkaz:
https://doaj.org/article/3f529b6c8bce439c8279e5911f4ff168
Autor:
Zhiyang Wang, Yongsheng Ou
Publikováno v:
Applied Sciences, Vol 12, Iss 5, p 2409 (2022)
Learning to master human intentions and behave more humanlike is an ultimate goal for autonomous agents. To achieve that, higher requirements for intelligence are imposed. In this work, we make an effort to study the autonomous learning mechanism to
Externí odkaz:
https://doaj.org/article/0b3af9a9560e4ef29d365d1c1f7602c5
Publikováno v:
Applied Sciences, Vol 9, Iss 10, p 2105 (2019)
The method of simultaneous localization and mapping (SLAM) using a light detection and ranging (LiDAR) sensor is commonly adopted for robot navigation. However, consumer robots are price sensitive and often have to use low-cost sensors. Due to the po
Externí odkaz:
https://doaj.org/article/25adbff474b64266a1866d0c84ef5c2e
Publikováno v:
Applied Sciences, Vol 9, Iss 7, p 1366 (2019)
The depth estimation of the 3D deformable object has become increasingly crucial to various intelligent applications. In this paper, we propose a feature-based approach for accurate depth estimation of a deformable 3D object with a single camera, whi
Externí odkaz:
https://doaj.org/article/fb869fcb71f842c2a5bae61a83cc6f26
Publikováno v:
Applied Sciences, Vol 9, Iss 1, p 41 (2018)
Simultaneous Localization and Mapping (SLAM) is an active area of robot research. SLAM with a laser range finder (LRF) is effective for localization and navigation. However, commercial robots usually have to use low-cost LRF sensors, which result in
Externí odkaz:
https://doaj.org/article/81acbf04cb6848a3b550e9630ffb181b