Prototype of a Line Follower Smart Car Using the A* Algorithm Approach for Shortest Path Finding

This study aims to design and build a prototype of a smart car designed to operate independently in detecting and following paths. This prototype utilizes image processing technology, specifically OpenCV, to recognize predetermined paths, enabling the car to move efficiently without human intervention. As the brain of the system, an ESP32 microcontroller is used to regulate movement and decision-making based on the results of image processing. In addition, this study also implements the A* algorithm for finding the closest route, which allows smart cars to calculate distances and determine optimal paths by considering various intersections and alternative routes. Testing was conducted on a simulated environment consisting of 9 nodes. The A* algorithm successfully calculated the optimal route A-B-D-F-H-I, with a total travel distance of 118 cm and a total heuristic of 1,122.7710081. The results of this study show that the prototype demonstrated sTable and responsive behaviour in detecting and following the path without human assistance.