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In ad-hoc human-robot collaboration (HRC), humans and robots work on a taskwithout pre-planning the robot's actions prior to execution; instead, taskallocation occurs in real-time. However, prior research has largely focused ontask allocations that are pre-planned - there has not been a comprehensiveexploration or evaluation of techniques where task allocation is adjusted inreal-time. Inspired by HCI research on territoriality and proxemics, we proposea design space of novel task allocation techniques including both explicittechniques, where the user maintains agency, and implicit techniques, where theefficiency of automation can be leveraged. The techniques were implemented andevaluated using a tabletop HRC simulation in VR. A 16-participant study, whichpresented variations of a collaborative block stacking task, showed thatimplicit techniques enable efficient task completion and task parallelization,and should be augmented with explicit mechanisms to provide users withfine-grained control.

"Grip-that-there": An Investigation of Explicit and Implicit Task Allocation Techniques for Human-Robot Collaboration