This study presents the design and implementation of a low-cost intelligent mobile robot capable of basic obstacle avoidance using an Arduino Uno microcontroller and HC-SR04 ultrasonic sensors. A lightweight avoidance algorithm was developed to enable real-time navigation decisions based on distance measurements. The robot was tested in controlled indoor environments (3 m × 3 m area) with 10 different obstacle configurations. Experimental results showed a 92% success rate in avoiding medium-sized static obstacles (objects >10 cm in width) and an 81% success rate in navigating around angled surfaces. The average response time was 245 ms, and the system maintained stable performance at voltages above 6.5 V. Below this threshold, detection accuracy dropped by 18%. A comparative evaluation against a similar platform using IR sensors revealed that the ultrasonic-based system improved detection range by 25% and reduced false-positive rates by 14%. However, the proposed system struggled with thin or low-profile obstacles, where performance was 63% successful. Despite these limitations, the prototype offers a scalable and cost-efficient platform for educational use. It also serves as a testbed for future integration of advanced technologies such as machine learning, and others. The study concludes with recommendations to enhance robustness through multi-sensor fusion, dynamic power management, and the development of adaptive control strategies for unstructured environments................. Keywords: ................Obstacle Avoidance, Arduino Uno, Ultrasonic Sensor, Mobile Robot, Real-Time Navigation, Comparative Evaluation, Embedded Systems