  Many of us researchers take extra measures to control for known-unknowns.
However, unknown-unknowns can, at best, be negligible, but otherwise, they
could produce unreliable data that might have dire consequences in real-life
downstream applications. Human-Robot Interaction standards informed by
empirical data could save us time and effort and provide us with the path
toward the robots of the future. To this end, we share some of our pilot
studies, lessons learned, and how they affected the outcome of our experiments.
While these aspects might not be publishable in themselves, we hope our work
might save time and effort for other researchers towards their research and
serve as additional considerations for discussion at the workshop.
