A SLAM Algorithm: A Superior Approach for Room Cleaning Robot

From the past few years, robot vacuum cleaners have made a huge impact on society and gained popularity as an automated cleaning solution Nowadays the vacuum cleaner robot uses a variety of mapping algorithms and navigational characteristics to function. Robots operate autonomously using these algorithms however, when the environment of a room or space changes it may not work efficiently in the new environment, requiring the user to teach it about the updated map. Sometimes, the robot takes time to understand the new room configuration. The vacuum cleaner robot should have a mechanism such as the artificial intelligence to solve the problem of cleaning the entire environment areas along with a navigation feature. For this, there are several algorithms but among the several mapping approaches, Simultaneous Localization and Mapping (SLAM) has become a standard technique, providing a reliable way to both map out unfamiliar locations and localize the robot on those maps at the same time. In this article, we have reviewed and analyzed different algorithms along with the SLAM algorithm and proved that the SLAM algorithm is the best approach for automated robots for navigation purposes._The comparison of the algorithms was mainly based on the data of several articles and projects. The results of simulation and comparison studies demonstrate that the SLAM algorithm is an appropriate approach for navigation purposes.