Alireza Naeini
Papers
1
Total Citations
1
H-Index
1
About
Alireza Naeini is a robotics researcher whose work focuses on advancing humanoid robot control, particularly in the domain of teleoperation and human motion imitation. His key research areas include inverse kinematics, artificial neural networks, and optimization algorithms for robotic systems. Naeini’s major contribution lies in his comparative study of ANN, ANFIS, and GA-optimized ANFIS for solving the inverse kinematics of the Surena-V humanoid’s arm—a critical challenge in enabling robots to replicate complex human movements for applications in automation, healthcare, and hazardous environments. This work, published in 2024, demonstrates his ability to bridge theoretical modeling with practical robotic implementation, offering insights into the trade-offs between accuracy and computational efficiency. While his citation count is currently modest, his research addresses a foundational problem in humanoid robotics, with potential implications for improving teleoperation systems. Naeini’s work is particularly relevant for students and researchers interested in the intersection of machine learning and robotics, as it highlights how optimization techniques can enhance the performance of humanoid robots in real-world tasks.
Research Focus
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Top Papers
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