Indoor Localization Using Low-Cost Sensors: Application to a ROS-Based Minicar

This study addresses the challenge of implementing autonomous navigation on a low-cost robotic platform—a minicar equipped with a Raspberry Pi 3 and the Robot Operating System (ROS). The primary focus is on achieving accurate localization using a simplified sensor setup consisting only of a gyroscope and an odometer. Unlike traditional approaches that rely on expensive and computationally intensive sensor arrays such as LiDAR or cameras, this method estimates the minicar's position and orientation through real-time sensor data processing. The system enables autonomous navigation within a predefined environment, tracking coordinates and displaying movement data on a terminal. This work demonstrates that cost-effective sensor configurations, when integrated with ROS and optimized algorithms, can achieve reliable localization, reducing hardware complexity and making autonomous systems more accessible for resource-constrained applications.