Papers
24
Total Citations
1,044
H-Index
14
About
Ahmed Rahmani is a prominent researcher specializing in multi-robot systems, distributed control, and intelligent optimization algorithms. His work sits at the intersection of autonomous robotics, control theory, and bio-inspired computing, with particular emphasis on coordinating teams of nonholonomic wheeled mobile robots in real-world environments. Rahmani's most impactful contributions center on distributed formation control for multiple mobile robots. His early foundational papers from 2013 — each accumulating over 147 citations — established key frameworks for both consensus-based and bioinspired neurodynamic approaches to leader–follower formation problems, effectively transforming complex multi-robot coordination into tractable state consensus problems. He subsequently extended this work by integrating adaptive neural networks and event-triggered control strategies, addressing real-world challenges such as model uncertainties and communication efficiency. His 2019 research on fixed-time consensus formation tracking under directed topologies further advanced the field's understanding of guaranteed convergence guarantees. More recently, Rahmani has pioneered learning-enhanced path planning algorithms, developing reinforcement learning and fractional-order variants of the Artificial Bee Colony algorithm, with his 2022–2023 publications already accumulating over 130 combined citations. Collectively, his body of work — exceeding 750 total citations — reflects sustained influence on autonomous multi-robot systems research and practical robotics applications.
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