Abstract
An intelligent automaton should always arrive at its goal automatically while avoiding the obstacles in a two-dimensional (2D) world. If the automaton does not know the shape or location of any obstacle in the world, it gathers information on its neighbourhood from some sensor, and according to the sensor information, it avoids the closer obstacles. In this situation, a sensor-based path-planning algorithm is used to determine the automaton's action flexibly according to changes in the sensor information. By this method, the automaton usually avoids the closer obstacles on the basis of the local information but it may circulate around some of the obstacles in the world because of the locality of the sensor information. If deadlock occurs, the automaton does not arrive at the goal at all. To overcome this drawback, we address a sufficient condition for designing a family of deadlock-free sensor-based path-planning algorithms in an uncertain world. Within this family, the automaton basically goes straight t...
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