AutoTracking + HandGesture Controlled Vehicle

We present a hybrid control system for a tracked vehicle that supports both gesture-based manual control and autonomous person tracking. The system enables users to steer the vehicle using a glove equipped with an STM32 microcontroller and MPU6050 accelerometer, which translates hand motions into real-time velocity commands via Wi-Fi communication. For autonomous operation, the vehicle uses an Intel RealSense RGB-D camera and a Jetson Nano running a YOLOv8-based object tracker to identify and follow a designated person. Linear and angular velocities are computed based on relative distance and lateral displacement, and a PID controller ensures smooth and accurate motor control through an STM32-based embedded system. This design enables flexible and intuitive human-vehicle interaction for assistive and robotic applications.