Automation of Surgical Procedures
Advancing the software, control, and decision-making needed for higher levels of autonomy in minimally invasive surgery.
We develop advanced control algorithms and intelligent autonomy frameworks that enable existing surgical robotic platforms to perform increasingly complex procedural tasks. Rather than designing new robotic hardware, our research focuses on the software, control, and decision-making required to support higher levels of autonomy in minimally invasive surgery.
Our work investigates shared autonomy, task-level automation, and intelligent control strategies that allow surgical robots to execute well-defined procedural subtasks safely and reliably while remaining under appropriate clinical supervision. By combining robotics, artificial intelligence, and human-robot interaction, we aim to create autonomous capabilities that augment surgeons, reduce cognitive workload, and improve procedural consistency across a wide range of minimally invasive interventions.
Collaborators
- University of Leeds clinical collaborators
- Industrial collaborators (Intuitive, CMR Surgical)
- International academic collaborators (Johns Hopkins University, Politecnico di Milano)
Publications
See our full list of publications on Google Scholar.