ANDROMEDA is an advanced medical robotics research platform focused on the development of autonomous robotic drilling technologies for neurosurgical applications, with particular emphasis on cranial bone drilling and craniotomy procedures. The project addresses key challenges associated with manual bone drilling, including limited precision, surgeon fatigue, variability in procedural execution, thermal damage, excessive mechanical loading, and uncontrolled drill breakthrough near sensitive intracranial structures.
The platform combines robotic manipulation, real-time sensing, force-controlled drilling, and intelligent safety mechanisms within a unified experimental framework for the development and validation of autonomous surgical workflows. The system integrates multi-modal sensing, including force, torque, temperature, and vision-based monitoring, together with closed-loop control algorithms and breakthrough detection strategies designed to improve surgical precision, repeatability, and procedural safety.
A major focus of the project is the development of intelligent drilling control methods using force regulation, predictive feedforward control based on preoperative imaging data, and real-time signal analysis. The platform supports research in autonomous surgical execution, sensor fusion, machine learning, surgical safety systems, and collaborative robotic assistance for medical procedures.
The project spans research activities from fundamental concept development (TRL1) to engineering design, prototype implementation, and laboratory validation in simulated surgical environments (TRL4). Experimental validation is performed using synthetic cranial bone models and sensorized drilling devices capable of capturing high-frequency process data during drilling operations.
In alignment with human-centric automation principles, ANDROMEDA emphasizes supervised autonomy and clinician oversight. The system is designed to autonomously execute well-defined procedural subtasks while maintaining full surgeon control over critical clinical decisions. The platform serves as an interdisciplinary environment for collaboration between robotics researchers, engineers, neurosurgeons, and industrial partners in the field of medical robotics and computer-assisted surgery.
The infrastructure supports scientific research, technology transfer, student theses, and development of future autonomous robotic systems for minimally invasive and image-guided surgical applications.