Abstract

This research explores the development and effectiveness of a two-wheeled balanced autonomous vehicle. Autonomous vehicles are capable of perceiving their environment and functioning without human intervention, gaining increasing attention due to their advanced automation capabilities. A fully autonomous system demonstrates self-awareness and independent decision-making. These vehicles utilize an array of sensors, actuators, machine learning algorithms, and high-performance processors to execute complex software tasks. The proposed two-wheeled autonomous vehicle achieves self-balancing through mechanisms such as PID or IADRC control systems and enables wireless steering via IoT connectivity using Bluetooth technology. Communication is facilitated through Java-based applications on mobile devices or personal computers. Equipped with radar sensors, the vehicle monitors nearby objects, while video cameras identify traffic lights, road signs, and pedestrians. Lidar technology aids in measuring distances, detecting road edges, and recognizing lane markings, and ultrasonic sensors ensure precise parking by identifying curbs and nearby obstacles. The innovative IADRC control system offers enhanced robustness, superior disturbance rejection, and effective obstacle avoidance. Additionally, the vehicle operates on clean energy, minimizing carbon emissions and contributing to environmental sustainability. Its potential applications include last-mile delivery services and other small-area operations, reinforcing its value as an eco-friendly and versatile solution for modern transportation challenges.