A major multi-institutional project aims to advance the implementation of fully autonomous surgical robots.
Caleb Rucker, PhD, B. Ray Thompson Professor in Mechanical, Aerospace and Biomedical Engineering at the University of Tennessee, recently joined a landmark multi-institutional project to help transform autonomous surgical robotics.
The project, awarded up to $12 million by the Advanced Research Projects Agency for Health (ARPA-H), is focused on developing a fully autonomous surgical robot that could one day perform complex surgeries without direct human intervention.
This cutting-edge endeavour centres on concentric tube robots – telescoping, super-elastic, needle-sized robotic devices that bend and extend precisely, resembling tentacles.
These robots are engineered from multiple nested, curved tubes that rotate and flex in coordination, enabling intricate manoeuvres within constrained anatomical spaces.
Vanderbilt University leads this ambitious initiative, directed by Robert J Webster, PhD, a prominent figure in mechanical engineering. His team comprises experts from the University of Utah, Johns Hopkins University, and Vanderbilt University Medical Centre, alongside hardware and software specialists from Virtuoso Surgical.
As co-principal Investigator, Dr Rucker leads the UT team in developing computational models that simulate both tissue response and robotic movements, which are integral to training the autonomous system.
These simulations will inform AI algorithms during training, optimise motion planning, and provide real-time surgical scene mapping.
Dr Rucker, who also directs a National Institutes of Health (NIH) project on concentric push-pull robots for colon surgery, said: ‘Working with a team at the forefront of AI, mechanical engineering, and clinical practice is incredibly exciting. This collaboration has the potential to advance robotic surgery well beyond current capabilities.’
Existing surgical robotics rely on two distinct automation methods: model-based automation, which uses predefined procedural sequences and set conditions, and machine-learning approaches, which require extensive procedural data for algorithm training.
While both methods involve advanced robotic surgery, each has limitations.
This project combines model-based and learning-based automation techniques, aiming to overcome these limitations and create an adaptable and interpretable system.
The research team envisions this new robotic system reaching anatomical areas currently inaccessible to surgical robots, such as autonomously removing tumours from the trachea and prostate. Potential applications extend to uterine fibroids, bladder tumours, spinal procedures, and brain cysts.
Dr Rucker said: ‘With robotic autonomy, we’re looking at increasing patient safety, reducing invasiveness and lightening the surgeon’s physical and cognitive demands. Our goal is a smaller, autonomous robotic system that operates on a scale well beyond what is achievable with today’s technology, offering transformative potential in surgical practice.’
