Abstract Details
  1. Home
  2. Abstract List
  3. Abstract Details
109 / 2025-02-22 23:19:46
Physics-Informed Neural Network-Based Adaptive Model Predictive Control for Visual Servoing of Robot Manipulators
image-based visual servoing,physics-informed neural networks,depth estimation,model predictive control,robot manipulator
Review group 13
Final Paper
Jiaqi Tang / Shanghai University of Electric Power
Qifang Liu / Shanghai University of Electric Power
Jianliang Mao / Shanghai University of Electric Power
Chuanlin Zhang / Shanghai University of Electric Power
In image-based visual servoing applications, the depth information of the feature points is inherently time-varying, which can lead to intractable computational challenges when conventional nonlinear model predictive control (NMPC) approaches are implemented. Furthermore, the depth information generally remains unavailable in vision-based measurements obtained through two-dimensional imaging systems. To address these challenges, a physics-informed neural network (PINN) is initially designed to compensate for these uncertain parameters minimizing the discrepancy between the linear system and the actual model. And that, by leveraging a more accurate model obtained through successive linearization, the adaptive model predictive control based on PINN (PINN-based AMPC) method is developed. The proposed control framework offers the advantage of generating relatively accurate system models with limited training data, while achieving rapid location of static object. Finally, the effectiveness of the proposed control method is demonstrated through a series of simulations conducted on a Universal Robots 3 (UR3) manipulator.
Important Date

  • Conference Date

    Jun 05

    2025

    to

    Jun 01

    2026

  • May 30 2025

    Draft paper submission deadline

  • Jun 08 2025

    Registration deadline

Sponsored By
China Southeast University
IEEE Power Electronics Society
Jiangsu Association of Automation
Nanjing Section IE Chapter
Organized By
Southeast University
Contact Information
Login to view full contact details
Previous Conferences