| Abstract: |  The aim of this thesis is to analyze the state-of-the-art of the currently available cloud services used for online localization of mobile robots performing urban search and rescue missions. Based on this analysis, a robust algorithm for localization of the mobile robot developed as a part of the Natural human-robot cooperation in dynamic environments (NIFTi) project was implemented in the Robot Operating System (ROS). The localization includes mainly the trajectory information in global world coordinates as well as markers corresponding the detected objects of interest. The result is visualized in the online map application.
To provide this localization algorithm with the suitable navigation data, a landmark based navigation algorithm was introduced. This relies on the computer vision and is based on the matching feature points between the actual camera view and the previously composed reference cloud of landmarks created locally (extension to the global navigation is discussed). For this purpose, the state-of-the-art techniques such as Structure from Motion, Speeded-Up Robust Features, and the Fast Approximate Nearest Neighbors were used.
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