What:

• Designed and constructed a 4 Degrees of Freedom (DOF) robotic arm for surgical tool tracking applications.

• Focused on creating a system adaptable for operating room settings, emphasizing precision and stability.

How:

• Applied mechanical design principles to fabricate the robotic arm, ensuring it meets performance requirements for adaptability and stability.

• Developed a foundation for integrating motion control algorithms to streamline surgical tool management in high-pressure environments.

• Collaborated on the integration of a machine-learning algorithm (YOLO11) to detect and label surgical instruments in real-time images.

Results:

• Achieved a 90% training accuracy and 66% validation accuracy with the YOLO11 model for real-time surgical instrument detection.

• Created a system ready for programming and implementation, enhancing efficiency and organization in surgical environments.