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Continuous Shape Estimation of Continuum Robots Using X-ray Images.

Edgar J Lobaton1, Jinghua Fu2, Luis G Torres2

  • 1Department of Electrical and Computer Engineering, North Carolina State University, USA.

IEEE International Conference on Robotics and Automation : ICRA : [Proceedings]. IEEE International Conference on Robotics and Automation
|August 18, 2015
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Summary
This summary is machine-generated.

This study introduces a novel method for precise, continuous shape estimation of continuum robots during medical procedures using minimal X-ray images. The technique improves accuracy by integrating robot kinematics with optimized X-ray viewpoints.

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Area of Science:

  • Medical Robotics
  • Image-Guided Interventions
  • Surgical Navigation

Background:

  • Continuum robots offer maneuverability in constrained anatomical spaces.
  • Accurate real-time shape estimation is vital for safe and effective continuum robot-assisted medical procedures.
  • Challenges include kinematic model uncertainty, robot motion, X-ray noise, and minimizing radiation exposure.

Purpose of the Study:

  • To develop a method for continuous and accurate online shape estimation of continuum robots during medical procedures.
  • To minimize X-ray imaging requirements while maintaining high shape estimation accuracy.
  • To address the complexities of shape estimation in dynamic and noisy environments.

Main Methods:

  • Integration of continuum robot kinematic models with data from optimally selected X-ray projection images.
  • Representation of robot shape as a deformable surface using time and space basis functions.
  • Utilizing probabilistic priors and numerical optimization for selecting optimal camera configurations to minimize estimation error.

Main Results:

  • The proposed method achieves significantly lower shape estimation errors compared to using kinematic models alone or random viewpoints.
  • Optimal selection of 3 to 10 X-ray viewpoints significantly enhances online shape estimation accuracy.
  • Demonstrated effectiveness in simulated concentric tube robot procedures.

Conclusions:

  • The developed method enables accurate and continuous online shape estimation for continuum robots in medical applications.
  • Optimized X-ray imaging strategies are crucial for improving the precision and safety of robot-assisted interventions.
  • This approach holds promise for enhancing surgical navigation and obstacle avoidance in minimally invasive procedures.