Arithmetic mean-based decision-making algorithm for obstacle avoidance and multiple intruder detection

Arif, M. U.; Marzoughi, Ali

doi:10.1109/anzcc50923.2020.9318343

Cited by 2 publications

(1 citation statement)

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“…A multi-sensor integration mechanism for mobile robot navigation is proposed in [5]. A novel method for the arithmetic mean-based decision-making system is described in [6]. Recently, there is a growing interest in fuzzy-controlled mobile robots [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Mobile Robot With Obstacle Avoidance Using Fuzzy Controller

Khudaverdiyeva

2022

A.I.S.

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This paper presents the modeling of a robot's navigation using ultrasonic sensors under uncertainty. The robot tries to avoid obstacles by using the fuzzy logic controller to process the data coming from three ultrasonic sensors. To assess the performance of fuzzy logic optimized robot navigation controller with ultrasonic sensors, which measure the distance by calculating the time spent on the object and its return, the obstacles are placed in front of, left, and right of the robot. Mamdani fuzzy reasoning system is used for the designed controller for its intuitive properties and fewer setting parameters which reduces the amount of time spent on the programming of the controller. 25 rules are considered to cover a robot’s possible interactions with obstacles. For an easy understanding of navigation architecture and rapid algorithm implementation, in this paper, a MATLAB simulation framework is developed. MATLAB/Simulink is one of the best simulation tools required to design the architecture and verify algorithms with real-time constraints. Resultant models of the fuzzy optimized controller demonstrate the superior performance of the fuzzy logic controller with high adaptability to the environment while maintaining a sufficient level of accuracy. The designed fuzzy controller can be used in microprocessor/microcontroller-based robots owing to easiness in implementation and coding.

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