A flexible path generator for a mobile robot

Mobile robots need a powerful and flexible navigation system in order to move around autonomously in an incompletely known and changing environment. The authors present a computational metaphor for path generation which is gleaned from fluid dynamics. It is powerful because it can find optimal paths in a maze of arbitrary complexity and it is flexible because it readily adapts to any change in the topology of the maze. They present a comparison between the fluid dynamics metaphor and other path planning methods and show that it does not suffer from local minima. They further discuss the natural parallelism of the metaphor and its implementation on the DAP computer.<>