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Related Experiment Video

Updated: Jul 4, 2026

Operation of the Collaborative Composite Manufacturing (CCM) System

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.

IEEE Robotics and Automation Letters

|July 3, 2026

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.

Keywords:

Computer Vision for Medical Robotics Laparoscopy Medical Robots and Systems Surgical Robotics

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Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound

Design and Implementation of a Bespoke Robotic Manipulator for Extra-corporeal Ultrasound

Published on: January 7, 2019

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.