Point cloud based environment mapping and localization in autonomous robots

With the development of engineering technology, the use of robots, which minimize the labor force of people in every field, has become widespread. The areas where robots are more preferred include space science, biomedical, machine industry, telecommunications and communication. The main reason for the frequent use of robots in the mapping area is to ensure the safety of life by making a preliminary exploration in areas where access is difficult and dangerous. Mapping robots can be designed in two different ways: semi-autonomous or fully autonomous. The autonomous feature of a robot can be provided with integrated sensors and the decision-making algorithms used. Autonomous robots need to know or discover the environment they are in to perform their functions. During the discovery of the environment, the robot must be able to determine its own position simultaneously. In the literature, this issue is known as Simultaneous Localization and Mapping (SLAM). In this thesis, a fully autonomous mapping robot was designed. Lidar Lite V3, a lidar sensor, has been chosen as a distance sensor. Lidar sensors are high-range laser distance sensors. Errors in the distance data from the Lidar sensor were eliminated by the filtering algorithms and a three-dimensional map of the environment was obtained and the autonomous robot was able to determine the location where it was located simultaneously.