Development of an adaptive fuzzy behavioural control system with experimental and industrial applications

Barfoot, Chris W; Ibrahim, M. Yousef

doi:10.1016/s0360-8352(98)00107-7

Cited by 2 publications

(1 citation statement)

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“…It is shown using simulation experiments that the proposed neuro-fuzzy system is able to improve navigation performance in complex and unknown environments. Barfoot and Ibrahim [7] discussed the development of an adaptive fuzzy behavioural control system for use with an autonomous mobile robot. Results on both experimental and industrial applications of their proposed control system were presented.…”

Section: Introductionmentioning

confidence: 99%

Motion control and navigation of multiple mobile robots for obstacle avoidance and target seeking: A rule-based neuro-fuzzy technique

Pradhan

Parhi

Panda

2008

Proceedings of the Institution of Mechanical Engineers, Part I:

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This paper describes a rule-based neuro-fuzzy technique for the navigation of 1000 robots in a cluttered environment. The planning and coordination between the mobile robots is extremely difficult. In the present analysis rule-based and rule-based neuro-fuzzy techniques are used to navigate multiple mobile robots in unknown and partially known environments. The aim of the robots is to reach a predefined goal. Based upon a reference motion, direction, distances between the robots and obstacles, and distances between the robots and targets, different types of rules are defined heuristically and refined later to find the steering angle. The control system combines a repelling influence related to the distance between robots and nearby obstacles and an attracting influence between the robots and targets. Then a hybrid rule-based neuro-fuzzy technique is analysed to find the steering angle of the robots. Simulation and experimental results show that the proposed rule-based neuro-fuzzy technique shows a better navigation performance in complex and unknown environments than the simple rule-based technique.

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Section: Introductionmentioning

confidence: 99%