A new novel approach to control the autonomous mobile robot that moved along a collision free trajectory until it reaches its target is proposed in this study. The development of autonomous mobile robots requires sophisticated navigation systems that enable them to operate efficiently in dynamic and unstructured environments. This paper presents a novel mobile robot navigation system leveraging a neuro-fuzzy rule-based optimization technique. The proposed system integrates neuro-fuzzy logic with optimization algorithms to enhance the robot's navigation capabilities, making it adept at obstacle avoidance, path planning, and adaptive learning. Experimental results demonstrate that the proposed system significantly improves navigation performance compared to traditional methods.
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Ali Majali (2024) studied this question.
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