Ahmad AlAttar
Imperial College London, University of Dubai, Dyson (United Kingdom)
Papers
6
Total Citations
68
H-Index
6
About
Ahmad AlAttar is a leading researcher in robotic manipulation, pioneering the field of kinematic-model-free (KMF) control. His work fundamentally challenges traditional robotics by enabling robots—from rigid manipulators to soft continuum robots—to learn and adapt without requiring prior knowledge of their mechanical structure. AlAttar’s major contributions include developing locally weighted dual quaternions for orientation control and integrating KMF methods with model predictive control for obstacle avoidance, as demonstrated in his highly cited 2020 and 2022 papers (18 and 15 citations, respectively). His innovative approach has proven effective in extreme environments, such as space operations with continuum manipulators, and in reconfigurable soft robots that grow and change shape. Notably, AlAttar also created an autonomous air-hockey playing cobot using optimal control and Bayesian tracking, showcasing the practical, real-world applicability of his theories. With a growing body of work accumulating over 70 citations, AlAttar is shaping the future of adaptive, model-free robotics, making his research essential for students and engineers working on next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
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