Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Ruiguang Hu"'
Publikováno v:
Drones, Vol 7, Iss 1, p 16 (2022)
Trajectory planning and obstacle avoidance play essential roles in the cooperative flight of multiple unmanned aerial vehicles (UAVs). In this paper, a unified framework for onboard distributed trajectory planning is proposed, which takes full advant
Externí odkaz:
https://doaj.org/article/d052b35f58c34e2d8d35ebbe41907a58
Publikováno v:
2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37b13e4f74aaabbea4c57ef133a4751b
https://doi.org/10.1109/iros47612.2022.9982096
https://doi.org/10.1109/iros47612.2022.9982096
Publikováno v:
Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control ISBN: 9789811939976
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a395ca14ca86f6439d537c0c2e24466a
https://doi.org/10.1007/978-981-19-3998-3_23
https://doi.org/10.1007/978-981-19-3998-3_23
Publikováno v:
2021 36th Youth Academic Annual Conference of Chinese Association of Automation (YAC).
In view of the multi-UAV cooperative area coverage search problem, the analysis and simplification are carried out. A number of improvement measures are proposed on the basis of the classic genetic algorithm to improve the adaptability of the algorit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9510f58108388bd9d232e4f10d92977e
https://doi.org/10.1109/yac53711.2021.9486677
https://doi.org/10.1109/yac53711.2021.9486677
Publikováno v:
2021 33rd Chinese Control and Decision Conference (CCDC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e51e33cc0d7e7c3c7d70f1799afd2931
https://doi.org/10.1109/ccdc52312.2021.9601717
https://doi.org/10.1109/ccdc52312.2021.9601717
Publikováno v:
2020 3rd International Conference on Unmanned Systems (ICUS).
The intelligent combat of aircraft has become an important research area. This paper studies the 1Vs1 pursuit-evasion game confrontation scenario of the aircraft, aiming to enable the red agent to find the optimal strategy to avoid the blue intercept
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cd3a880069fa818dc229302adf235df
https://doi.org/10.1109/icus50048.2020.9274907
https://doi.org/10.1109/icus50048.2020.9274907
Publikováno v:
AOPC 2020: Optical Sensing and Imaging Technology.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::adf8c68762b0b38735983256199dd2ef
https://doi.org/10.1117/12.2579575
https://doi.org/10.1117/12.2579575
Publikováno v:
MIPPR 2019: Pattern Recognition and Computer Vision.
As an excellent method for extracting distinctive invariant features from images, SIFT (scale-invariant feature transform) can effectively resist affine transformation such as translation and rotation of images, and theoretically has better resistanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ce40c66cb7de461e345dd4db40737a1
https://doi.org/10.1117/12.2535592
https://doi.org/10.1117/12.2535592
Publikováno v:
MIPPR 2019: Pattern Recognition and Computer Vision.
Aiming at the vehicle target detection problem of multi-polarization SAR image under the terrain backgrounds, the global CFAR detection by dual-polarized 16-bit data is proposed, which effectively reduces the influence of terrain clutter on detection
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99e1825ea3e9ea304bcbbac2eb79cbf7
https://doi.org/10.1117/12.2535015
https://doi.org/10.1117/12.2535015
Publikováno v:
MIPPR 2019: Pattern Recognition and Computer Vision.
In this paper, heterogeneous features extraction is conducted by deep learning for drug-related webpages classification. First, body text and image-label text are extracted through HTML parsing, and effective images are chosen by the FOCARSS algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fbcf2568eb2f8e3cd48dec1044cde3d7
https://doi.org/10.1117/12.2535014
https://doi.org/10.1117/12.2535014