This thesis presents the design and implementation of a motion control system intended for a real-time vision-based tracking application. The goal was to track a coloured, free-falling water droplet using lowcost hardware. For initial system verification, a coloured splash ball was used as a proxy target, chosen for its higher visibility and consistent shape. The system integrated a Raspberry Pi 5 with a Raspberry Pi HQ Camera and a Pimoroni PIM183 pan–tilt unit for vertical target tracking. A PD controller adjusted the tilt angle based on positional data to track and centre the target. To compensate for approximately 100 ms of actuation latency, along with additional delays introduced by processing and computation, the PD controller used predicted target positions. These were provided by an Extended Kalman Filter, which was configured to forecast motion 160 ms ahead. Experimental results showed that the splash ball remained in view for approximately 40–50% of its fall duration. Accurate centring was not achieved, as delays in actuator response limited the system’s ability to keep pace with the high velocity of the target. Furthermore, water droplet tracking proved to be infeasible, as the detection system could not detect such small targets. These findings indicate that, due to hardware-induced delays, the system was unable to achieve stable tracking of high-velocity targets.