Alireza K. Tehrani
Tarbiat Modares University, Islamic Azad University, Science and Research Branch
Papers
3
Total Citations
40
H-Index
3
About
Alireza K. Tehrani is a leading researcher in the field of robotics, with a primary focus on the kinematic control of redundant manipulators. His work addresses the fundamental challenge of inverse kinematics, which is computationally expensive and can cause significant control delays in real-time applications. For redundant robots—which possess more degrees of freedom than necessary—this problem is compounded by the need for optimization among infinite possible solutions. Tehrani’s major contributions include the development of adaptive fuzzy logic algorithms that not only solve inverse kinematics efficiently but also enable obstacle avoidance by modeling obstacles as convex bodies and updating fuzzy rule bases in real time. His 2003 paper, "An optimized adaptive fuzzy inverse kinematics solution for redundant manipulators," and his 1999 work on obstacle avoidance each have garnered 14 citations, demonstrating sustained impact. Notably, his 2010 paper, "A Dual Neural Network for Kinematic Control of Redundant Manipulators Using Input Pattern Switching," introduces a neural network approach that further advances real-time control. Tehrani’s innovative fusion of fuzzy logic, optimization, and neural networks has provided practical, human-inspired solutions for complex robotic systems, making his research essential for students and engineers working on autonomous manipulation and intelligent control.
Research Focus
Key Achievements
Top Papers
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