Offline 2D Map for Self-driving Vehicle Model

Navigation plays a significant role in modern robotics, allowing autonomous robots to navigate and move in space. In the 21st century, navigation technologies in robotics have made significant strides. One of the key developments has been the widespread adoption of lidar sensors, which have become more powerful, compact, and, most importantly, more affordable. While in the 2000s, the cost of these sensors was in the tens or even hundreds of thousands of dollars, by the 2020s, it had dropped to just thousands of dollars. This fact has played a crucial role in the development of autonomous vehicles, and lidar sensors continue to evolve to this day. This research project aims to create a 2D map of indoor spaces using lidar scans of the environment taken by a robot. The practical significance of the project lies in improving the navigation of an unmanned vehicle indoors, allowing it to build routes based on the generated map of the real environment.