Mohammad Saraee

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About

Mohammad Saraee’s research lies at the intersection of robotics, artificial intelligence, and optimization, with a particular focus on autonomous navigation systems. His most cited work, “A new path planner for autonomous mobile robots based on genetic algorithm” (2010, 13 citations), addresses a fundamental challenge in robotics: enabling robots to navigate complex environments with speed and precision. By applying genetic algorithms to local path planning, Saraee developed a method that balances immediate path design with high accuracy and efficiency—critical for real-time autonomous operations. This contribution reflects his broader interest in leveraging evolutionary computation to solve dynamic, constraint-heavy problems in robotics. Beyond this flagship paper, Saraee’s research portfolio spans intelligent systems and data-driven decision-making, demonstrating a commitment to bridging theoretical optimization with practical engineering. His work has informed subsequent studies in autonomous navigation and algorithm design, earning recognition for its practical utility. For students and researchers exploring robotics or AI, Saraee’s approach offers a clear example of how bio-inspired algorithms can enhance machine autonomy in unpredictable settings.