ABSTRACT
Algorithms used in autonomous robots are listed. The principles and main steps of the Simultaneous Localization and Mapping (SLAM) algorithm are described. It is an algorithm that helps the robot build a map of the environment and find its location within that map. Different versions of the SLAM algorithm are discussed, viz., visual SLAM and LiDAR SLAM. Common SLAM algorithms are mentioned, e.g., extended Kalman filter (EKF-SLAM), FastSLAM, and GraphSLAM. The main steps, important considerations, and applications of the artificial potential field algorithm are elaborated upon. This algorithm simulates a possible field in which attractive forces pull the robot toward the goal while repulsive forces push it away from obstacles. The components of the proportional-integral-derivative algorithm, its steps, key aspects, and applications are reviewed. It is a feedback control algorithm that works by adjusting a controller output. The advantages and limitations of these algorithms are outlined.
