Zead Mohammed Yosif

Papers

Total Citations

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About

Zead Mohammed Yosif is a researcher specializing in mobile robotics and artificial intelligence, with a particular focus on autonomous navigation and obstacle avoidance. His work centers on developing intelligent control systems that enable mobile robots to navigate complex, dynamic environments without human intervention. Yosif’s most cited paper, "Artificial Techniques Based on Neural Network and Fuzzy Logic Combination Approach for Avoiding Dynamic Obstacles" (2022, 4 citations), introduces a hybrid AI framework that integrates A* path planning with neural network-based zone classification and fuzzy logic for real-time obstacle avoidance. This approach represents a significant contribution to creating low-cost, efficient navigation solutions for autonomous robots. His earlier work, "Assessment and Review of the Reactive Mobile Robot Navigation" (2021, 2 citations), provides a comprehensive evaluation of reactive navigation algorithms, highlighting the growing importance of artificial intelligence in robotics. Yosif’s research is particularly relevant for applications in hazardous environments where human operation is risky, and his findings help advance the development of safer, more autonomous robotic systems. His work continues to influence the integration of soft computing techniques in mobile robot navigation.