A R Khoobkar

About

A. R. Khoobkar is a researcher whose work bridges computational intelligence and robotics, with a particular focus on the application of neural networks to complex engineering problems. His most cited paper, "GMDH Type Neural Networks and Their Application to the Identification of the Inverse Kinematics Equations of Robotic Manipulators" (2005), demonstrates his key contribution: using Group Method of Data Handling (GMDH) neural networks to solve the challenging inverse kinematics problem in robotics, offering a data-driven alternative to traditional analytical methods. This work, with 7 citations, has provided a foundation for researchers exploring neural network-based control and identification in robotic systems. Khoobkar’s research is notable for its practical engineering focus, aiming to enhance the accuracy and efficiency of robotic manipulators through intelligent modeling. His contributions are particularly relevant for students and researchers in mechatronics and control systems, as they showcase how neural architectures can be tailored to specific mechanical tasks. By integrating GMDH networks with robotics, Khoobkar has helped advance the field of soft computing in engineering applications.

Research Focus

Key Achievements

Top Papers

1. 1
   GMDH Type Neural Networks and Their Application to the Identification of the Inverse Kinematics Equations of Robotic Manipulators (RESEARCH NOTE)

   7 citations · 2005

Key Collaborators

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