A Machine Learning Method for Vision-Based Unmanned Aerial Vehicle Systems to Understand Unknown Environments

What makes unmanned aerial vehicles (UAVs) intelligent is their capability of sensing and understanding new unknown environments. Some studies utilize computer vision algorithms like Visual Simultaneous Localization and Mapping (VSLAM) and Visual Odometry (VO) to sense the environment for pose estim...

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Detalles Bibliográficos
Autores principales: Zhang, Tianyao, Hu, Xiaoguang, Xiao, Jin, Zhang, Guofeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308845/
https://www.ncbi.nlm.nih.gov/pubmed/32517309
http://dx.doi.org/10.3390/s20113245

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7308845/
https://www.ncbi.nlm.nih.gov/pubmed/32517309
http://dx.doi.org/10.3390/s20113245

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