Mohammadamin Samadi Khoshkho
Papers
1
Total Citations
9
H-Index
1
About
Mohammadamin Samadi Khoshkho is a robotics researcher whose work centers on the dynamic control of continuum robots—flexible, cable-driven manipulators designed to operate in confined and unstructured environments. His most-cited paper, "Distilled neural state-dependent Riccati equation feedback controller for dynamic control of a cable-driven continuum robot" (2023, 9 citations), introduces a novel learning-based optimal control approach that addresses key challenges in this domain, including nonlinear coupling, dynamic uncertainty, and the complexities of real-time interaction with unpredictable surroundings. By distilling a neural network policy from a state-dependent Riccati equation (SDRE) controller, Khoshkho achieves robust, computationally efficient feedback control that outperforms traditional methods. This work is notable for bridging model-based control and data-driven learning, offering a practical solution for high-precision tasks in medical robotics, search-and-rescue, and industrial inspection. With a growing citation record, his contributions are gaining traction among researchers seeking to enhance the autonomy and reliability of continuum robots. Khoshkho’s research stands out for its technical rigor and direct applicability to real-world robotic systems operating under tight spatial and dynamic constraints.
Research Focus
Key Achievements
Top Papers
- 1