  With an increasing interest in human-robot collaboration, there is a need to
develop robot behavior while keeping the human user's preferences in mind.
Highly skilled human users doing delicate tasks require their robot partners to
behave according to their work habits and task constraints. To achieve this, we
present the use of the Optometrist's Algorithm (OA) to interactively and
intuitively personalize robot-human handovers. Using this algorithm, we tune
controller parameters for speed, location, and effort. We study the differences
in the fluency of the handovers before and after tuning and the subjective
perception of this process in a study of $N=30$ non-expert users of mixed
background -- evaluating the OA. The users evaluate the interaction on trust,
safety, and workload scales, amongst other measures. They assess our tuning
process to be engaging and easy to use. Personalization leads to an increase in
the fluency of the interaction. Our participants utilize the wide range of
parameters ending up with their unique personalized handover.
