Papers
10
Total Citations
202
H-Index
7
About
Ali Aflakian is a robotics and control systems researcher whose work spans cable-driven parallel robots, haptic devices, visual servoing, and—most recently—autonomous disassembly for sustainable manufacturing. His early contributions established strong foundations in experimental robotics: his 2018 studies on kinematic control of cable-suspended parallel robots (49 citations) and dynamic identification of the Novint Falcon haptic device (41 citations) demonstrated a rigorous blend of theoretical modeling and hands-on validation. His development of phase-trajectory-length-based oscillation damping for cable-driven systems (31 citations) further solidified his reputation in nonlinear control. Aflakian's research has since pivoted toward high-impact sustainability challenges. His pioneering telerobotics work for electric vehicle battery disassembly (40 citations) addresses critical barriers in EV recycling—safety uncertainty, design complexity, and limited standardisation—making it one of his most socially relevant contributions. Complementing this, he has advanced hybrid visual servoing techniques that improve manipulability and overcome classical convergence and singularity problems, with applications in automating battery disassembly workflows. His more recent investigations into reinforcement learning, curriculum-based domain randomisation, and contact-rich task learning reflect a forward-looking trajectory toward intelligent, adaptable robotic systems. With over 200 cumulative citations, Aflakian's body of work meaningfully bridges experimental control engineering and next-generation autonomous robotics.
Research Focus
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Top Papers
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- 7Optimized hybrid decoupled visual servoing with supervised learning9 citations · 2021
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