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About

Mumtaj Begam is a robotics researcher whose work centers on intelligent control systems, mobile robot navigation, and humanoid robotics. Her most influential contributions focus on applying fuzzy logic techniques to enhance the autonomy and adaptability of robotic systems. In her highly cited 2010 paper, she developed a fuzzy logic-based controller for differential drive wheeled mobile robots, enabling active target tracking and reactive obstacle avoidance in unstructured environments—a foundational approach that has garnered 25 citations. She extended this work with a fuzzy-based navigation and control framework for non-holonomic mobile robots, demonstrating how human-like reasoning can be computationally integrated into robotic control (20 citations). Beyond mobile robotics, Begam has made notable contributions to dexterous manipulation, modeling and simulating a multi-fingered robot hand for grasping tasks using Solidworks and Adams software (9 citations). Her research also encompasses bipedal locomotion and humanoid arm kinematics, where she has addressed coordinate transformation challenges for movement planning. With a career spanning foundational work in fuzzy control and humanoid design, Begam’s research continues to influence autonomous robotics, particularly in navigation, manipulation, and biomimetic systems.