Skip to main content
King Abdullah University of Science and Technology
Statistics
Statistics
  • Study
    • Prospective Students
    • Current Students
  • Research
    • Research Areas
    • Research Groups
  • People
    • All People
    • Faculty
    • Affiliate Faculty
    • Instructional Faculty
    • Research Scientists
    • Research Staff
    • Postdoctoral Fellows
    • Administrative Staff
    • Alumni
    • Students
  • News
  • Events
  • History
  • Al-Kindi
    • Al-Kindi Distinguished Statistics Lectures
    • Al-Kindi Student Awards
  • About
  • CEMSE Division
  • Apply

NMPC

Model Predictive Control and Imitation Learning Algorithms for Robot Motion Planning in Physical Human-Robot Interaction

Aigerim Nurbayeva, Postdoctoral Research Fellow, Electrical and Computer Engineering
Mar 15, 12:00 - 13:00

B9 R2325

Model Predictive Control robotics deep neural networks Numerical Optimization universal robot human-robot interactions NMPC

This seminar presents a framework for safe and efficient human-robot workspace sharing by using Deep Neural Networks (DNN) and safety filters to rapidly imitate computationally heavy Nonlinear Model Predictive Control method (NMPC), with successful experimental validation on a UR5 manipulator.

Statistics (STAT)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice

Disclaimer: The views and opinions expressed in this page are strictly those of the page author. The contents of this page have not been reviewed or approved by the King Abdullah University of Science and Technology.