Soniya Yeasmin

Khulna University of Engineering and Technology

Papers

Total Citations

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About

Dr. Soniya Yeasmin is a researcher specializing in intelligent robotics and adaptive control systems, with a particular focus on integrating machine learning techniques to enhance robotic autonomy. Her most cited work, "GA-based adaptive fuzzy logic controller for a robotic arm in the presence of moving obstacle" (2017), addresses the critical challenge of automating the design of fuzzy logic controllers for articulated robot platforms—a process traditionally complex and time-consuming. By employing genetic algorithms (GA) to optimize fuzzy logic parameters, she developed a system that enables robotic arms to dynamically adapt to moving obstacles, significantly improving real-time decision-making and obstacle avoidance capabilities. This contribution has garnered attention in the field, with 4 citations reflecting its foundational role in advancing adaptive control methodologies. Dr. Yeasmin’s research bridges the gap between theoretical machine learning and practical robotics, offering scalable solutions for industrial automation and human-robot interaction. Her work underscores the potential of evolutionary algorithms to streamline controller design, making her a notable voice in the intersection of computational intelligence and robotic systems.