A microsurgical robot research platform for robot-assisted microsurgery research and training

Area of Science:

• Robotics
• Surgical Technology
• Medical Simulation

Background:

• Microsurgery, including ocular, ENT, and neurosurgery, requires specialized training.
• Current platforms often cater to macro-scale surgery, lacking dedicated microsurgical solutions.
• Robot-assisted microsurgery (RAMS) adoption necessitates advanced research and training tools.

Purpose of the Study:

• To introduce a novel microsurgical robot research platform (MRRP) for research and clinical training.
• To address the limitations of existing platforms in microsurgical skill development.
• To facilitate advancements in robot-assisted microsurgery.

Main Methods:

• Developed a hardware system featuring a bimanual slave robot, master controllers, and a vision system.
• Implemented an extensible software architecture using the robot operating system.
• Explored and compared master-slave mapping strategies and different user interfaces.

Main Results:

• Experimental validation included trajectory following and targeting tasks for training evaluation.
• User studies demonstrated the hybrid interface's superiority over traditional methods.
• The hybrid interface improved task completion time, reduced clutching frequency, and enhanced ease of control.

Conclusions:

• The MRRP provides an objective platform for microsurgical skills training using motion and vision data.
• The system supports the verification of high-level control algorithms for RAMS.
• It enables task automation research and development in robot-assisted microsurgery.