  In ad-hoc human-robot collaboration (HRC), humans and robots work on a task
without pre-planning the robot's actions prior to execution; instead, task
allocation occurs in real-time. However, prior research has largely focused on
task allocations that are pre-planned - there has not been a comprehensive
exploration or evaluation of techniques where task allocation is adjusted in
real-time. Inspired by HCI research on territoriality and proxemics, we propose
a design space of novel task allocation techniques including both explicit
techniques, where the user maintains agency, and implicit techniques, where the
efficiency of automation can be leveraged. The techniques were implemented and
evaluated using a tabletop HRC simulation in VR. A 16-participant study, which
presented variations of a collaborative block stacking task, showed that
implicit techniques enable efficient task completion and task parallelization,
and should be augmented with explicit mechanisms to provide users with
fine-grained control.
