Papers
8
Total Citations
147
H-Index
5
About
Zouhaier Affi is a robotics researcher whose work centers on the kinematic analysis, error modeling, and design optimization of parallel manipulators, with a particular focus on translational parallel robots. His most influential contribution — "Prediction of the pose errors produced by joints clearance for a 3-UPU parallel robot" (2009, 96 citations) — established him as a leading voice in understanding how mechanical imperfections, such as joint clearances and design parameter uncertainties, affect robot accuracy. This foundational work spawned a productive research thread exploring error estimation, sensitivity analysis, and orientation error prediction across multiple parallel manipulator architectures, including the 3-UPU and 3-TPM platforms. Affi has made notable methodological contributions by integrating interval analysis, Newton-Euler formalism, and genetic algorithms with the Krawczyk operator to develop robust optimization frameworks that simultaneously minimize robot positioning errors and maximize design tolerances. His comparative precision studies further help engineers select between competing manipulator designs. Validated against established simulation tools such as ADAMS, his models bridge theoretical rigor and practical applicability. With a career spanning over fifteen years and work cited internationally, Affi's research provides essential tools for engineers designing high-precision parallel robotic systems in manufacturing and automation contexts.
Research Focus
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