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About

Awais Gul Khan is a robotics and control systems researcher whose work sits at the intersection of autonomous navigation, robotic manipulation, and robust control theory. His most recognized contribution, a hierarchical path planning framework for wheeled mobile robots navigating partially known uneven terrain (2022, 50 citations), addresses one of the field's enduring challenges — enabling robots to make intelligent motion decisions despite incomplete environmental information. This work has established him as a notable voice in autonomous ground vehicle research. Beyond navigation, Khan has developed a focused body of work on the precise control of robotic manipulators, tackling the practically critical problems of input deadzone nonlinearities, external disturbances, and internal uncertainties. His contributions span adaptive control strategies, finite-time sliding mode controllers, and continuous integral sliding mode approaches, collectively demonstrating a systematic effort to push manipulator control toward greater robustness and real-world applicability. His 2024 adaptive control paper has already garnered 10 citations, reflecting growing community interest. His more recent work on Luenberger-like interval observers signals an expanding interest in state estimation for uncertain dynamic systems. Across his portfolio, Khan consistently bridges theoretical rigor with engineering relevance, making his research valuable to both control theorists and robotics practitioners.