Visual metric and semantic localization for UGV

Visual metric and semantic localization for UGV

During the continual transitions from lab research to real-world applications of vision-based algorithms, there are significant challenges, e.g. the robustness to adapt to complex environments and the high demands of multi-task, multi-modal learning models. More specifically on visual simultaneous l...

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Bibliographic Details
Main Author: Zhang, Handuo
Other Authors: Mao Kezhi
Format: Thesis-Doctor of Philosophy
Language:English
Published: Nanyang Technological University 2022
Subjects:
Engineering::Electrical and electronic engineering::Control and instrumentation::Robotics
Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Online Access:https://hdl.handle.net/10356/162442

Internet

https://hdl.handle.net/10356/162442

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