N. Khoshraftar

Papers

Total Citations

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About

N. Khoshraftar is a researcher specializing in robotics, particularly the kinematics and control of parallel mechanisms. Their most cited work, "Forward Kinematics Solution of Stewart-Gough using Improved Hybrid Strategy (Neural Network and 3rd-order Newton-Raphson)" (2017), addresses the computationally intensive Forward Kinematics Problem (FKP) for parallel robots. By integrating neural networks with a third-order Newton-Raphson method, Khoshraftar developed a hybrid algorithm that significantly reduces solution time while maintaining accuracy—a critical advancement for real-time applications in flight simulators, machine tools, and medical robotics. This contribution, though early in their career, has garnered 2 citations, reflecting its niche but practical impact. Khoshraftar’s work bridges classical robotics theory with modern machine learning, offering a streamlined approach to solving complex kinematic equations. Their research underscores a commitment to enhancing the efficiency of robotic systems, making them more responsive and reliable. As a rising voice in robotics, Khoshraftar continues to explore innovative computational strategies, positioning themselves as a promising contributor to the field’s evolution toward smarter, faster, and more adaptable robotic platforms.