This study investigates the use of WiFi signal strength for localization and navigation in low-cost robotic systems, focusing on indoor environments. Mathematical models are developed based on signal strength measurements, integrated with triangulation techniques for dynamic robot positioning. Both logarithmic and linear regression techniques are employed to determine the distances between the robot and access points. Through experimental verification, accurate localization abilities are showcased. Various navigation algorithms, including A*, are evaluated for effectiveness. Overall, this study presents a low-cost system for indoor autonomous positioning and navigation, with potential applications in home care, inventory management, and emergency support.