Morteza Alebooyeh
Papers
4
Total Citations
88
H-Index
4
About
Morteza Alebooyeh is a robotics researcher specializing in collaborative robotics, kinematics modeling, and flexible material handling automation. His work sits at the intersection of industrial automation, machine learning, and advanced manufacturing — areas with growing relevance in automotive and aerospace industries. Alebooyeh's most recognized contribution is his 2019 neural network-based framework for solving the forward and inverse kinematics of the 7-DOF ABB YuMi collaborative robot, which has garnered 38 citations and remains a valuable reference for researchers working with high-degree-of-freedom manipulators. By combining analytical modeling with visual workspace representation, this work significantly simplifies a classically complex problem in robot motion planning. His subsequent research tackled a particularly challenging industrial problem: automating the handling of limp, flexible materials such as fiber composites used in lightweight vehicle manufacturing. Through systematic investigation of gripper configurations and performance across fabric pick-and-place scenarios — work accumulating over 46 combined citations — Alebooyeh advanced practical solutions for robotic manipulation of deformable materials. His more recent 2024 study extends this line of inquiry using finite element modeling techniques, underscoring his commitment to bridging simulation and real-world robotic deployment in advanced manufacturing contexts.
Research Focus
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Top Papers
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