Self-organizing system for the motion planning of mobile robots

Mobile robots need a powerful and flexible navigation system in order to move around autonomously in an incompletely known and changing environment. We present a computational metaphor for path generation which is gleaned from fluid dynamics. It is powerful for two reasons. First it can find in a maze of arbitrary complexity nearly optimal paths: they are as short as possible without passing too closely to the obstacles. Second it is flexible because it readily adapts to any change in the topology of the maze. We compare our method with the artificial potential method and related approaches and show by a topological analysis that the fluid dynamics metaphor has distinctive advantages. The paper further discusses the natural parallelism of the metaphor, its implementation on the DAP computer and examines some possible extensions by showing that additional constraints on the path can be tackled using the fluid metaphor.