Robotics Vector Control Demo

This project focused on the development and validation of an autonomous SMARTcar platform using model-based design and real-world testing in Simulink and embedded hardware. The system combined velocity control, steering control, optical path following, ultrasonic parking assistance, and battery monitoring into a complete robotics control workflow.

A PI-based velocity controller was designed and tuned in Simulink to regulate the vehicle speed during both simulation and hardware experiments. Steering behavior was implemented using optical sensors that detected the position of black tape on the track, allowing the vehicle to perform autonomous path following and maneuvering. Lookup tables and experimentally measured sensor data were used to improve the realism and accuracy of the steering model.

The project included both simulation-based and real-world validation of the vehicle dynamics. Tests compared cornering radius, steering response, and tracking performance between the software model and the physical SMARTcar platform. Results demonstrated close agreement at low speeds while also highlighting practical limitations such as wheel slip, steering bias, and sensor noise in hardware operation.

Additional functionality included an ultrasonic sensor system for autonomous parking detection and a battery management subsystem capable of monitoring individual cell voltages and estimating battery state of charge. These systems were integrated and validated through experimental testing, creating a complete embedded robotics platform that combined control theory, sensor fusion, simulation, and real-time autonomous behavior.