In this project we implement SLAM (Simultaneous Localization and Mapping) for a 2 dimensional world. It combines robot sensor measurements and movement to create a map of an environment from only sensor and motion data gathered by a robot, over time. SLAM gives a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features. This is an active area of research in the fields of robotics and autonomous systems.
The project consists of several relatively independent parts:
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Jupyter notebooks
Provide detailed explanations of SLAM algorithm and implementation guidelines.
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C++ console application
Basic implementation of Graph SLAM in C++ without GUI.
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Qt application
Features visualization of robot movement and localization.
Setup details for each sub-project can be found under corresponding project folders.