The Autonomous Obstacle-Avoidance Robot project focuses on designing and implementing a self-navigating robotic system capable of detecting obstacles and dynamically adjusting its path in real-time. The project demonstrates practical applications of robotics, automation, and intelligent mobility systems, combining sensors, microcontrollers, and motor control to achieve collision-free movement. The system is built using an Arduino microcontroller as the brain of the robot, controlling DC motors for movement and ultrasonic sensors for obstacle detection. The ultrasonic sensors continuously measure the distance between the robot and surrounding objects. Using this data, the Arduino dynamically calculates an optimal path to avoid collisions while maintaining smooth navigation. The robot’s control logic is implemented via Arduino programming, enabling autonomous decision-making based on sensor inputs. If an obstacle is detected in front of the robot, it can stop, turn, or choose an alternative path, ensuring safe and efficient movement. The system is capable of navigating through complex environments, demonstrating real-time responsiveness and adaptability to changing surroundings. This project highlights hands-on skills in electronics, robotics, and automation. It integrates motor drivers, sensors, and microcontroller programming to create a functional autonomous system. By combining hardware and software, the robot exemplifies the principles of intelligent mobility and autonomous navigation, providing a foundation for advanced robotics applications. The project also offers practical experience in debugging, tuning sensor thresholds, and optimizing motor responses. It can be expanded for additional features like line-following, remote control, or IoT-based monitoring, showcasing the scalability and versatility of Arduino-based robotic systems. Overall, the project demonstrates the ability to design, implement, and test a real-time autonomous robot, emphasizing automation, obstacle avoidance, and intelligent mobility as key components of modern robotics engineering.