Aigerim Nurbayeva
Papers
4
Total Citations
78
H-Index
4
About
Aigerim Nurbayeva is a robotics researcher whose work centers on human-robot interaction, motion planning, and control systems for safe, collaborative robotics. Her major contributions lie in developing accessible, open-source technologies and intelligent control frameworks that enable robots to work alongside humans without compromising safety. Her most cited paper (27 citations) presents an open-source, 7-DOF wireless human arm motion-tracking system, democratizing inertial motion capture for researchers and educators. She has advanced deep imitation learning to replicate nonlinear model predictive control (NMPC) laws, achieving safe physical human-robot interaction (23 citations), and pioneered shared control of manipulators with obstacle avoidance using deep reinforcement learning (21 citations). Her recent work on NMPC with set terminal constraints further refines safe robot motion planning under speed and separation monitoring protocols. With over 78 cumulative citations, Nurbayeva’s research bridges theoretical control methods and practical deployment, making her a notable contributor to the field of collaborative robotics.
Research Focus
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Top Papers
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