ShopMate

Abstract

This project aims to enhance the shopping experience by helping customers easily locate items without prior knowledge of the supermarket layout. It saves time, reduces confusion, and supports individuals such as elderly people or first-time visitors. The system introduces automation and smart navigation into everyday retail environments, promoting the concept of intelligent shopping. The project focuses on several key aspects, including accurate indoor navigation to ensure autonomous and safe movement, collision avoidance using LiDAR, ultrasonic, accelerometer, gyroscope, and speed sensors, item scanning to allow users to view product prices and track their total cost, user-friendly interaction for entering shopping lists, and efficient path planning to minimize walking distance. The main objectives are to design and implement an autonomous cart that guides users to desired items, ensures smooth and safe movement through multi-sensor integration, and simplifies the shopping process by providing real-time product information. The methodology involves defining hardware and software components, using LiDAR for real-time mapping and localization, developing path-planning and obstacle-avoidance algorithms, integrating data from multiple sensors for stability, and building a simple user interface for inputting lists and scanning products. While some experimental smart carts exist globally, this project has not been developed before at our university, particularly not in this integrated form combining autonomous navigation with real-time LiDAR mapping and product price scanning.