  Integrating mobile robots into human society involves the fundamental problem
of navigation in crowds. This problem has been studied by considering the
behaviour of humans at the level of individuals, but this representation limits
the computational efficiency of motion planning algorithms. We explore the idea
of representing a crowd as a flow field, and propose a formal definition of
path quality based on the concept of invasiveness; a robot should attempt to
navigate in a way that is minimally invasive to humans in its environment. We
develop an algorithmic framework for path planning based on this definition and
present experimental results that indicate its effectiveness. These results
open new algorithmic questions motivated by the flow field representation of
crowds and are a necessary step on the path to end-to-end implementations.
