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27 November 2024

New software developed to support surgical robotics

Researchers from the School of Biomedical Engineering & Imaging Sciences have successfully integrated KUKA's Fast Robot Interface (FRI) with ROS 2 and Python, significantly enhancing the capabilities of the surgical robot.

Man and woman standing near KUKA robot arm

KUKA’s LBR Med robot has been adapted to meet specific medical requirements and is perfectly suited for a wide range of assistance systems in medical technology on account of its human-robot collaboration capability.

The LBR-Stack project has developed an integration that simplifies the usage of these robots in real-time applications, providing robust support for both simulation and real hardware communication.

The potential impact of the project is substantial, particularly in the fields of medical robotics and industrial automation which is the research team’s primary interest.

Ultimately, this software makes the robot part of a bigger and more flexible ecosystem. This enables surgeons to contribute novel and less restrictive workflows that are tailored to the patient’s specific needs. From an engineering perspective, the software allows for full hardware abstraction, which will help iterate systems quicker and drive down cost in the future.

Dr Martin Huber, PhD Student, School of Biomedical Engineering & Imaging Sciences, King’s College London

The project includes various packages such as Python bindings and ROS 2 integration, making it the most comprehensive solution for developers and researchers working with KUKA robots.

By offering a single, unified framework that works with multiple FRI versions, the project makes building robotic applications smoother and faster.

The project has garnered significant attention, with over 150 stars on GitHub, a platform that allows developers to create, store, manage and share their code. Indicating its potential for global reach and the community's recognition of its value.

The investigators behind this achievement are Martin Huber, Christopher E. Mower, Professor Sebastien Ourselin, Professor Tom Vercauteren, and Professor Christos Bergeles from the School of Biomedical Engineering & Imaging Sciences at King’s College London.

Read the full paper here.

In this story

Martin Huber

PhD Student

Christos  Bergeles

Professor of Surgical Robotics

Sebastien Ourselin

Professor of Healthcare Engineering

Tom  Vercauteren

Professor of Interventional Image Computing