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.