• DOI:10.1109/iros.2006.282190
Corpus ID: 12284900

A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks

@article{Mayer2006ASF,
  title={A System for Robotic Heart Surgery that Learns to Tie Knots Using Recurrent Neural Networks},
  author={H. Mayer and F. Gomez and Daan Wierstra and I. Nagy and A. Knoll and J. Schmidhuber},
  journal={2006 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2006},
  pages={543-548}
}

• H. Mayer, F. Gomez, +3 authors J. Schmidhuber
• Published 2006
• Computer Science
• 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

Tying suture knots is a time-consuming task performed frequently during minimally invasive surgery (MIS). Automating this task could greatly reduce total surgery time for patients. Current solutions to this problem replay manually programmed trajectories, but a more general and robust approach is to use supervised machine learning to smooth surgeon-given training trajectories and generalize from them. Since knottying generally requires a controller with internal memory to distinguish between… Expand

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