Data-driven Visual Servoing of Flexible Continuum Robots in Constrained Environments

Abstract

This paper presents a data-driven visual servoing framework for flexible continuum robots operating in constrained environments. By leveraging learning-based models to handle system uncertainty and nonlinear deformation, the proposed approach achieves robust and accurate visual servoing performance in real-time robotic manipulation tasks.

Main Contributions

• Data-driven visual servoing framework for continuum robots
• Robust control under uncertainty and environmental constraints
• Experimental validation on flexible robotic platforms

Citation

@INPROCEEDINGS{11246163,
  author    = {Chen, Wei and Wu, Haiwen and Dong, Xiyue and Yang, Bohan and Liu, Yun-Hui},
  booktitle = {2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  title     = {Data-driven Visual Servoing of Flexible Continuum Robots in Constrained Environments},
  year      = {2025},
  pages     = {20746--20751},
  doi       = {10.1109/IROS60139.2025.11246163}
}