Nasrin Kalamian

About

Nasrin Kalamian’s research focuses on advancing the control and locomotion of bipedal robots, with a particular emphasis on navigating complex, obstacle-filled environments. Her major contributions lie in the application of Nonlinear Model Predictive Control (NMPC) to enable dynamic walking and obstacle stepping without the need for pre-planned trajectories—a significant challenge in robotics. Her most-cited work, "Dynamic walking of biped robots with obstacles using predictive controller" (2011, 11 citations), demonstrates how NMPC allows biped robots to step over large obstacles autonomously, while a companion paper (2011, 6 citations) further refines this approach. Kalamian has also innovated in control theory, designing a suboptimal controller that combines the Riccati equation with a state-dependent impulsive observer for robotic manipulators (2019, 5 citations), and more recently, she integrated an enhanced disturbance observer with NMPC to improve walking stability on smooth surfaces (2021, 3 citations). Her work bridges theoretical control methods and practical robotic challenges, offering scalable solutions for legged locomotion.

Research Focus

Key Achievements

Top Papers

1. 1
   Dynamic walking of biped robots with obstacles using predictive controller

   11 citations · 2011
2. 2
   Stepping of biped robots over large obstacles using NMPC controller

   6 citations · 2011
3. 3
   Design of a Suboptimal Controller based on Riccati Equation and State-dependent Impulsive Observer for a Robotic Manipulator

   5 citations · 2019
4. 4
   On the Design of a Nonlinear Model Predictive Controller based on Enhanced Disturbance Observer for Dynamic Walking of Biped Robots

   3 citations · 2021

Key Collaborators

Contact & Links