<![CDATA[Service robots are becoming increasingly essential in offices or domestic environments, usually called domestic service robots (DSR). They must navigate and interact seamlessly with their surroundings, including humans and objects, which relies on effective mapping and localization. This study focuses on mapping, employing the light detection and ranging (LiDAR) sensor. The sensor, tested at proximity, gathers distance data to generate two-dimensional maps on a mini-PC. Additionally, it provides rotational positioning and robot odometry, broadening coverage through robot movement. A microcontroller with wireless smartphone connectivity facilitates control via Bluetooth. The robot is also equipped with ultrasonic sensors serving as a bumper. Testing in rooms of varying sizes using three methods (i.e., Hector simultaneous localization and mapping (SLAM), Google Cartographer, and real-time appearance-based mapping (RTAB-Map)) yielded good quality maps. The best F1-measure value was 96.88% achieved by Google Cartographer. All the results demonstrated the feasibility of this approach for DSR development across diverse applications.]]>
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