The field of human-robot interaction deals with robotic systems that involve

humans and robots closely interacting with each other. With these systems

getting more complex, users can be easily overburdened by the operation

and can fail to infer the internal state of the system or its ”intentions”. A

social robot, replicating the human eye region with its familiar features and

movement patterns, that are the result of years of evolution, can counter

this. However, the replication of these patterns requires hard- and software

that is able to compete with the human characteristics and performance.

Comparing previous systems found in literature with the human capabili-

ties reveal a mismatch in this regard. Even though individual systems solve

single aspects, the successful combination into a complete system remains

an open challenge. In contrast to previous work, this thesis targets to close

this gap by viewing the system as a whole — optimizing the hard- and

software, while focusing on the replication of the human model right from

the beginning. This work ultimately provides a set of interlocking building

blocks that, taken together, form a complete end-to-end solution for the de-

sign, control, and evaluation of a human-inspired robotic eye. Based on the

study of the human eye, the key driving factors are identified as the success-

ful combination of aesthetic appeal, sensory capabilities, performance, and

functionality. Two hardware prototypes, each based on a different actua-

tion scheme, have been developed in this context. Furthermore, both hard-

ware prototypes are evaluated against each other, a previous prototype, and

the human by comparing objective numbers obtained by real-world mea-

surements of the real hardware. In addition, a human-inspired and model-

driven control framework is developed out, again, following the predefined

criteria and requirements. The quality and human-likeness of the motion,

generated by this model, is evaluated by means of a user study. This frame-

work not only allows the replication of human-like motion on the specific

eye prototype presented in this thesis, but also promotes the porting and

adaption to less equipped humanoid robotic heads. Unlike previous systems

found in literature, the presented approach provides a scaling and limiting

function that allows intuitive adjustments of the control model, which can

be used to reduce the requirements set on the target platform. Even though

a reduction of the overall velocities and accelerations will result in a slower

motion execution, the human characteristics and the overall composition of

the interlocked motion patterns remain unchanged.