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Updated: Jul 4, 2026

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Operation of the Collaborative Composite Manufacturing (CCM) System
Published on: October 1, 2019
Stable Tracking-in-the-Loop Control of Cable-Driven RCM Surgical Manipulators under Erroneous Kinematic Chains
Neelay Joglekar1, Fei Liu2, Florian Richter3
1Neelay Joglekar is with the Robotics Institute in the School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Summary
We developed a stable controller for out-of-view joints in Remote Center of Motion (RCM) robotic surgery manipulators. This addresses critical errors in cable-driven systems, paving the way for more autonomous surgical procedures.
Area of Science:
- Robotics
- Surgical Technology
- Control Systems
Background:
- Remote Center of Motion (RCM) robotic manipulators are crucial for Minimally Invasive Surgery (MIS).
- Accurate control of RCM tools is essential for autonomous surgical subtasks and improved patient outcomes.
- Cable-driven RCM systems suffer from joint reading errors that compromise kinematic computations.
Purpose of the Study:
- To address irreparable kinematic errors in the out-of-view portion of RCM manipulator chains.
- To design and validate a provably stable tracking-in-the-loop controller for these unobservable errors.
- To advance the transition from teleoperated to autonomous robotic surgery.
Main Methods:
- Developed a novel tracking-in-the-loop controller specifically for the out-of-view kinematic chain.
- Integrated this controller into a bilevel control scheme for the entire RCM manipulator.
- Conducted rigorous benchmarking in both simulated and real-world experimental settings.
Main Results:
- Demonstrated a provably stable control strategy for previously uncorrectable joint errors in RCM manipulators.
- Validated the controller's effectiveness through comprehensive simulations and physical experiments.
- Provided empirical evidence supporting the theoretical stability findings.
Conclusions:
- The developed controller effectively compensates for out-of-view joint errors in RCM systems.
- This work establishes a foundation for enhancing the reliability of autonomous robotic surgery.
- Key insights are provided for future advancements in surgical robotics and automation.
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