Design of a service robot for restaurant applications using Lidar-Based SLAM localization

In this study, we propose the design of a table-running robot intended for deployment in restaurant environments, aiming to automate food service operations while enhancing safety and accuracy. The proposed robot employs a multi-sensor fusion localization method, integrating data from a LIDAR sensor, wheel encoders, an accelerometer, and a gyroscope. Unlike systems that rely on magnetic tape for navigation, our approach utilizes a SLAM (Simultaneous Localization and Mapping) algorithm to process sensor data and construct a dynamic map of the environment. This enables the robot to navigate flexibly and reroute in response to moving obstacles. Additionally, we introduce a localization method using V-L markers, allowing the robot to autonomously locate and dock with its charging station when battery levels are low. Experimental results confirm the robot's accurate and reliable performance in real-world conditions.