This paper suggests a new exploration strategy of an autonomous mobile robot in an unknown environment. Determination of a temporary goal based on a representation of work area named exploration quadtree is proposed. The exploration quadtree provides the information on quality of the regions concerned in a robot’s workspace. Using this quadtree the robot easily finds the next temporary goal that makes exploration more efficient. The quadtree is made up from a sonar probability map that is constructed by sonar range sensing and Bayesian probability theory. We then propose a method that plans a path between the determined temporary goals based on a probability map. The developed methods were implemented on a real mobile robot, AMROYS-II, which was built in our laboratory, and shown to be useful enough in a real environment that can be projected onto a two-dimensional space.

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