Abstract
Navigation of autonomous mobile robots in dynamic and unknown environments needs to take into account different kinds of uncertainties. Type-1 fuzzy logic research has been largely used in the control of mobile robots. However, type-1 fuzzy control presents limitations in handling those uncertainties as it uses precise fuzzy sets. Indeed type-1 fuzzy sets cannot deal with linguistic and numerical uncertainties associated with either the mechanical aspect of robots, or with dynamic changing environment or with knowledge used in the phase of conception of a fuzzy system. Recently many researchers have applied type-2 fuzzy logic to improve performance. As control using type-2 fuzzy sets represents a new generation of fuzzy controllers in mobile robotic issue, it is interesting to present the performances that can offer type-2 fuzzy sets by regards to type-1 fuzzy sets. The paper presented deep and new comparisons between the two sides of fuzzy logic and demonstrated the great interest in controlling mobile robot using type-2 fuzzy logic. We deal with the design of new controllers for mobile robots using type-2 fuzzy logic in the navigation process in unknown and dynamic environments. The dynamicity of the environment is depicted by the presence of other dynamic robots. The performances of the proposed controllers are represented by both simulations and experimental results, and discussed over graphical paths and numerical analysis.
Highlights
JILSA in mobile robot control by fuzzy logic, all the cited forms of uncertainties will be multiplied over fuzzification, inference and defuzzification
We deal with the design of new controllers for mobile robots using type-2 fuzzy logic in the navigation process in unknown and dynamic environments
In this paper we presented T2 controllers for mobile robot navigation
Summary
In mobile robot control by fuzzy logic, all the cited forms of uncertainties will be multiplied over fuzzification, inference and defuzzification. The results showed that type-2 fuzzy logic outperforms its type-1 counterpart This was shown through robot paths and control surfaces. In [27], an interval type-2 fuzzy logic was proposed for the control of a robot tracking a mobile object in the context of robot soccer games. To evaluate the performance of the type-2 fuzzy logic against its type-1 counterpart, graphical paths analysis were presented showing the way the player reaches the position of the ball. In this paper we propose specific aspects of control of mobile robots in unknown and dynamic environments using type-2 fuzzy logic.
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