A novel approach to integrate artificial potential field and fuzzy logic into a common framework for robots autonomous navigation

Artificial potential field and fuzzy logic are efficient approaches for mobile robots autonomous navigation. However, both have advantages and drawbacks. Their integration into a common control scheme can significantly improve the performances of the resulting hybrid controller. In this article, we propose a novel hybrid approach in order to better exploit their advantages. The present work contributes in three aspects: first, the proposed control scheme integrates interval type-2 fuzzy logic concepts with artificial potential field concepts into a common framework in order to better exploit their advantages. Second, the proposed control scheme is a simple and realizable design for real-time implementation because only 15 fuzzy rules are sufficient to control the mobile robot. Third, the proposed control scheme is a synthesized design which utilizes both heuristic knowledge and the sampled input–output data pairs. An implementation in real-time on an omnidirectional mobile robot validates the effectiveness of the proposed control scheme.

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