A fully autonomous robot needs a flexible map to solve frequent change of robot situations and/or tasks. In this paper, based on the second type of fuzzy modeling, fuzzy potential energy (FPE) is proposed to build a map that facilitates planning robot tasks for real paths. Three rules for making use of FPEs are derived to ground the basic ideas of building a map for task navigation. How the FPE performs robot navigation is explained by its gradient directions and shown by its gradient trajectories. To code qualitative information into quantity, the proposed FPE provides a way to quickly find a path for conducting the designated task or solving a robot under an embarrassing situation. This paper pioneers novel design and application of fuzzy modeling for a special map that exploits innovation usage of task navigation for real paths. Actually, visibility graphs based on the knowledge of human experts are employed to build FPE maps for navigation. To emphasize the idea of the created FPE, seven remarks direct the roadmap towards being a utility tool for robot navigation. Three illustrative examples, containing three spatial patterns, doors, corridors and cul-de-sacs, are also included. This paper paves the way to create ideas of intelligent navigation for further developments.
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