Assistive Mobile Robot Navigation and Localization using FastSLAM Algorithm

This study introduces a novel technique to improve a mobile robot's ability to move and navigate on its own in uncharted territory. Robots can navigate a normal human workstation on their own thanks to simultaneous localization and mapping technologies. The SLAM technique is mostly used for mapping and localization in static environments. In this study, a special FastSLAM algorithm augmentation that includes a module for tracking individuals using 2D Lidar sensor data is designed and evaluated. The SLAM algorithm may filter measurements from those measures because of the noise generated by people walking is unstable and dynamic by nature. This has been tested with our mobile robot platform for social support. This approach has a more accurate localization and a clearer depiction of the mapping of the environment. Overall, the range of mobile assistive robots is broad and is expanding as new uses are found and technology develops. These robots have the potential to make a big influence on a lot of different businesses and enhance a lot of different elements of daily life.