Md. Mahedi Al Arafat

Papers

Total Citations

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About

Md. Mahedi Al Arafat is an emerging researcher in robotics and intelligent systems, with a focused interest in autonomous navigation and obstacle avoidance. His most-cited work, "Neural Network-Based Obstacle and Pothole Avoiding Robot" (2023), introduces a novel application of neural networks to enable robots to detect and circumvent both obstacles and road hazards like potholes—a practical contribution to field robotics and autonomous vehicle safety. Though early in his career, with this paper garnering 2 citations, it signals a promising trajectory in integrating machine learning with real-world robotic challenges. Al Arafat’s research bridges the gap between theoretical AI models and tangible, deployable solutions for unstructured environments. His work is particularly relevant for students and researchers exploring cost-effective, neural-driven navigation systems, and it underscores the growing importance of adaptive robotics in infrastructure monitoring and assistive technologies. As he continues to build his portfolio, Al Arafat’s contributions reflect a commitment to solving practical problems through intelligent automation.