Loss of an eye is a tragedy for a person, who may suffer psychologically and physically. This thesis is concerned with the design, sensing and control of a robotic prosthetic eye that moves horizontally in synchronization with the movement of the natural eye.

Two generations of robotic prosthetic eye models have been developed. The first generation model uses external infrared sensor array mounted on the frame of a pair of eye glasses to detect the natural eye movement and to feed the control system to drive the artificial eye to move with the natural eye. The second generation model removes the impractical usage of the eye glass frame mounted external sensors and instead uses the human brain EOG (electrooculargraph) signal picked up by electrodes placed on the sides of a person’s head to carry out the same eye movement detection and control tasks as mentioned above.

Theoretical issues on sensor reliability, sensor failure detection and recovery, and signal processing techniques used in sensor data fusion are studied using statistical methods and artificial neural network based techniques.

In addition, practical control system design and implementation using micro controllers are studied and implemented to carry out the natural eye movement detection and artificial robotic eye control tasks. Simulation and experimental studies are performed and the results are included to demonstrate the effectiveness of the thesis research project reported in this document.