Papers
8
Total Citations
164
H-Index
6
About
Amal Meddahi is a leading researcher in industrial robotics, whose work centers on the optimization of robotized tasks, simulation platforms, and advanced control systems. Her major contributions lie in the development of genetic algorithm-based methods for time scheduling and trajectory optimization, directly addressing the industrial imperative to maximize productivity and reduce cycle costs. Her most cited work, “Time scheduling and optimization of industrial robotized tasks based on genetic algorithms” (57 citations), exemplifies this focus. Meddahi is also the creator of IRoSim, an innovative CAD-based platform for simulation, design, and planning, which integrates mechanical and robotics software to streamline development processes. Beyond optimization, her research extends to decentralized observers for multi-agent systems and the frontier of soft material manufacturing, including wrinkle-free robotic sewing. With a cumulative impact of over 160 citations, Meddahi’s work bridges theoretical algorithms and practical industrial applications, offering tools and methodologies that enhance robot placement, task efficiency, and manufacturing flexibility. Her achievements make her a pivotal figure for students and researchers interested in the future of intelligent, automated manufacturing.
Research Focus
Key Achievements
Top Papers
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- 3Genetic Algorithms based method for time optimization in robotized site25 citations · 2010
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- 7A decentralized observer for a general class of Lipschitz systems5 citations · 2013
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